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Yu J, Yan N, Gong Z, Ma Q, Liu J, Wu X, Deng G. Mycobacterium manipulate glutaminase 1 mediated glutaminolysis to regulate macrophage autophagy for bacteria intracellular survival. Cell Signal 2024; 124:111422. [PMID: 39307377 DOI: 10.1016/j.cellsig.2024.111422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2024] [Revised: 09/09/2024] [Accepted: 09/16/2024] [Indexed: 09/27/2024]
Abstract
Autophagy plays a vital role in eliminating intracellular mycobacterium. It is regulated by multiple metabolic processes including glutaminolysis. Glutaminase 1 (GLS1) is the rate-limiting enzyme of glutaminolysis and has been reported to control intracellular Gln content. However, its function on regulating autophagy in mycobacterium infected macrophage is still obscure. Hence, the current study hired mycobacterium virulent strain H37Rv or attenuated strain BCG to infect macrophage and detected the changes in cell glutaminolysis. The function of GLS1 on regulating autophagy in mycobacterium infected macrophages was further investigated. The results showed that BCG infection promoted macrophage autophagy, enhanced glutaminolysis, reduced intracellular Gln content, accompanied with the up-regulation of GLS1. Conversely, H37Rv infection resulted in completely opposite effects. Meanwhile, knockdown of GLS1 increased Gln content and attenuated autophagy in BCG infected macrophages. In addition, the deprivation of Gln not only promoted the autophagy of H37Rv infected macrophages, but also abolished the effect of knockdown GLS1 on regulating BCG infection-induced mTOR activation or autophagy. To sum up, our study suggested that different virulent strains of mycobacterium infection have totally opposite effects on glutaminolysis and the expression of GLS1. Specifically, mycobacterium virulent strain reduced GLS1 expression and decreased Gln content but mycobacterium attenuated strain promoted GLS1 expression and enhanced Gln content. Furthermore, GLS1 inhibits the activation of the mTOR signaling pathway and promotes autophagy by decreasing Gln content.
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Affiliation(s)
- Jialin Yu
- School of Life Science, NingXia University, Yinchuan, NingXia, 750021, China; Key lab of ministry of education for protection and utilization of special biological resources in western China, NingXia University, Yinchuan, NingXia, 750021, China
| | - Na Yan
- School of Life Science, NingXia University, Yinchuan, NingXia, 750021, China; Key lab of ministry of education for protection and utilization of special biological resources in western China, NingXia University, Yinchuan, NingXia, 750021, China
| | - Zhaoqian Gong
- School of Life Science, NingXia University, Yinchuan, NingXia, 750021, China; Key lab of ministry of education for protection and utilization of special biological resources in western China, NingXia University, Yinchuan, NingXia, 750021, China
| | - Qinmei Ma
- School of Life Science, NingXia University, Yinchuan, NingXia, 750021, China; Key lab of ministry of education for protection and utilization of special biological resources in western China, NingXia University, Yinchuan, NingXia, 750021, China
| | - Jing Liu
- The Fourth People's Hospital of Ningxia Hui Autonomous Region, Yinchuan, Niangxia, 750021, China
| | - Xiaoling Wu
- School of Life Science, NingXia University, Yinchuan, NingXia, 750021, China; Key lab of ministry of education for protection and utilization of special biological resources in western China, NingXia University, Yinchuan, NingXia, 750021, China.
| | - Guangcun Deng
- School of Life Science, NingXia University, Yinchuan, NingXia, 750021, China; Key lab of ministry of education for protection and utilization of special biological resources in western China, NingXia University, Yinchuan, NingXia, 750021, China.
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Bohórquez JA, Adduri S, Ansari D, John S, Florence J, Adejare O, Singh G, Konduru NV, Jagannath C, Yi G. A novel humanized mouse model for HIV and tuberculosis co-infection studies. Front Immunol 2024; 15:1395018. [PMID: 38799434 PMCID: PMC11116656 DOI: 10.3389/fimmu.2024.1395018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2024] [Accepted: 04/25/2024] [Indexed: 05/29/2024] Open
Abstract
Background Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), continues to be a major public health problem worldwide. The human immunodeficiency virus (HIV) is another equally important life-threatening pathogen. HIV infection decreases CD4+ T cell levels markedly increasing Mtb co-infections. An appropriate animal model for HIV/Mtb co-infection that can recapitulate the diversity of the immune response in humans during co-infection would facilitate basic and translational research in HIV/Mtb infections. Herein, we describe a novel humanized mouse model. Methods The irradiated NSG-SGM3 mice were transplanted with human CD34+ hematopoietic stem cells, and the humanization was monitored by staining various immune cell markers for flow cytometry. They were challenged with HIV and/or Mtb, and the CD4+ T cell depletion and HIV viral load were monitored over time. Before necropsy, the live mice were subjected to pulmonary function test and CT scan, and after sacrifice, the lung and spleen homogenates were used to determine Mtb load (CFU) and cytokine/chemokine levels by multiplex assay, and lung sections were analyzed for histopathology. The mouse sera were subjected to metabolomics analysis. Results Our humanized NSG-SGM3 mice were able to engraft human CD34+ stem cells, which then differentiated into a full-lineage of human immune cell subsets. After co-infection with HIV and Mtb, these mice showed decrease in CD4+ T cell counts overtime and elevated HIV load in the sera, similar to the infection pattern of humans. Additionally, Mtb caused infections in both lungs and spleen, and induced granulomatous lesions in the lungs. Distinct metabolomic profiles were also observed in the tissues from different mouse groups after co-infections. Conclusion The humanized NSG-SGM3 mice are able to recapitulate the pathogenic effects of HIV and Mtb infections and co-infection at the pathological, immunological and metabolism levels and are therefore a reproducible small animal model for studying HIV/Mtb co-infection.
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Affiliation(s)
- José Alejandro Bohórquez
- Department of Cellular and Molecular Biology, The University of Texas Health Science Center at Tyler, Tyler, TX, United States
- Center for Biomedical Research, The University of Texas Health Science Center at Tyler, Tyler, TX, United States
- Department of Medicine, The University of Texas at Tyler School of Medicine, Tyler, TX, United States
| | - Sitaramaraju Adduri
- Department of Cellular and Molecular Biology, The University of Texas Health Science Center at Tyler, Tyler, TX, United States
- Center for Biomedical Research, The University of Texas Health Science Center at Tyler, Tyler, TX, United States
| | - Danish Ansari
- Department of Cellular and Molecular Biology, The University of Texas Health Science Center at Tyler, Tyler, TX, United States
- Center for Biomedical Research, The University of Texas Health Science Center at Tyler, Tyler, TX, United States
- Department of Medicine, The University of Texas at Tyler School of Medicine, Tyler, TX, United States
| | - Sahana John
- Department of Cellular and Molecular Biology, The University of Texas Health Science Center at Tyler, Tyler, TX, United States
- Center for Biomedical Research, The University of Texas Health Science Center at Tyler, Tyler, TX, United States
- Department of Medicine, The University of Texas at Tyler School of Medicine, Tyler, TX, United States
| | - Jon Florence
- Department of Cellular and Molecular Biology, The University of Texas Health Science Center at Tyler, Tyler, TX, United States
- Center for Biomedical Research, The University of Texas Health Science Center at Tyler, Tyler, TX, United States
| | - Omoyeni Adejare
- Department of Cellular and Molecular Biology, The University of Texas Health Science Center at Tyler, Tyler, TX, United States
- Center for Biomedical Research, The University of Texas Health Science Center at Tyler, Tyler, TX, United States
| | - Gaurav Singh
- Department of Medicine, The University of Texas at Tyler School of Medicine, Tyler, TX, United States
| | - Nagarjun V. Konduru
- Department of Cellular and Molecular Biology, The University of Texas Health Science Center at Tyler, Tyler, TX, United States
- Center for Biomedical Research, The University of Texas Health Science Center at Tyler, Tyler, TX, United States
| | - Chinnaswamy Jagannath
- Department of Pathology and Genomic Medicine, Center for Infectious Diseases and Translational Medicine, Houston Methodist Research Institute, Houston, TX, United States
| | - Guohua Yi
- Department of Cellular and Molecular Biology, The University of Texas Health Science Center at Tyler, Tyler, TX, United States
- Center for Biomedical Research, The University of Texas Health Science Center at Tyler, Tyler, TX, United States
- Department of Medicine, The University of Texas at Tyler School of Medicine, Tyler, TX, United States
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3
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Demicheva E, Dordiuk V, Polanco Espino F, Ushenin K, Aboushanab S, Shevyrin V, Buhler A, Mukhlynina E, Solovyova O, Danilova I, Kovaleva E. Advances in Mass Spectrometry-Based Blood Metabolomics Profiling for Non-Cancer Diseases: A Comprehensive Review. Metabolites 2024; 14:54. [PMID: 38248857 PMCID: PMC10820779 DOI: 10.3390/metabo14010054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 01/05/2024] [Accepted: 01/12/2024] [Indexed: 01/23/2024] Open
Abstract
Blood metabolomics profiling using mass spectrometry has emerged as a powerful approach for investigating non-cancer diseases and understanding their underlying metabolic alterations. Blood, as a readily accessible physiological fluid, contains a diverse repertoire of metabolites derived from various physiological systems. Mass spectrometry offers a universal and precise analytical platform for the comprehensive analysis of blood metabolites, encompassing proteins, lipids, peptides, glycans, and immunoglobulins. In this comprehensive review, we present an overview of the research landscape in mass spectrometry-based blood metabolomics profiling. While the field of metabolomics research is primarily focused on cancer, this review specifically highlights studies related to non-cancer diseases, aiming to bring attention to valuable research that often remains overshadowed. Employing natural language processing methods, we processed 507 articles to provide insights into the application of metabolomic studies for specific diseases and physiological systems. The review encompasses a wide range of non-cancer diseases, with emphasis on cardiovascular disease, reproductive disease, diabetes, inflammation, and immunodeficiency states. By analyzing blood samples, researchers gain valuable insights into the metabolic perturbations associated with these diseases, potentially leading to the identification of novel biomarkers and the development of personalized therapeutic approaches. Furthermore, we provide a comprehensive overview of various mass spectrometry approaches utilized in blood metabolomics research, including GC-MS, LC-MS, and others discussing their advantages and limitations. To enhance the scope, we propose including recent review articles supporting the applicability of GC×GC-MS for metabolomics-based studies. This addition will contribute to a more exhaustive understanding of the available analytical techniques. The Integration of mass spectrometry-based blood profiling into clinical practice holds promise for improving disease diagnosis, treatment monitoring, and patient outcomes. By unraveling the complex metabolic alterations associated with non-cancer diseases, researchers and healthcare professionals can pave the way for precision medicine and personalized therapeutic interventions. Continuous advancements in mass spectrometry technology and data analysis methods will further enhance the potential of blood metabolomics profiling in non-cancer diseases, facilitating its translation from the laboratory to routine clinical application.
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Affiliation(s)
- Ekaterina Demicheva
- Institute of Natural Sciences and Mathematics, Ural Federal University, Ekaterinburg 620075, Russia; (V.D.); (F.P.E.); (K.U.); (A.B.); (E.M.); (O.S.); (I.D.)
- Institute of Immunology and Physiology of the Ural Branch of the Russian Academy of Sciences, Ekaterinburg 620049, Russia
| | - Vladislav Dordiuk
- Institute of Natural Sciences and Mathematics, Ural Federal University, Ekaterinburg 620075, Russia; (V.D.); (F.P.E.); (K.U.); (A.B.); (E.M.); (O.S.); (I.D.)
| | - Fernando Polanco Espino
- Institute of Natural Sciences and Mathematics, Ural Federal University, Ekaterinburg 620075, Russia; (V.D.); (F.P.E.); (K.U.); (A.B.); (E.M.); (O.S.); (I.D.)
| | - Konstantin Ushenin
- Institute of Natural Sciences and Mathematics, Ural Federal University, Ekaterinburg 620075, Russia; (V.D.); (F.P.E.); (K.U.); (A.B.); (E.M.); (O.S.); (I.D.)
- Autonomous Non-Profit Organization Artificial Intelligence Research Institute (AIRI), Moscow 105064, Russia
| | - Saied Aboushanab
- Institute of Chemical Engineering, Ural Federal University, Ekaterinburg 620002, Russia; (S.A.); (V.S.); (E.K.)
| | - Vadim Shevyrin
- Institute of Chemical Engineering, Ural Federal University, Ekaterinburg 620002, Russia; (S.A.); (V.S.); (E.K.)
| | - Aleksey Buhler
- Institute of Natural Sciences and Mathematics, Ural Federal University, Ekaterinburg 620075, Russia; (V.D.); (F.P.E.); (K.U.); (A.B.); (E.M.); (O.S.); (I.D.)
| | - Elena Mukhlynina
- Institute of Natural Sciences and Mathematics, Ural Federal University, Ekaterinburg 620075, Russia; (V.D.); (F.P.E.); (K.U.); (A.B.); (E.M.); (O.S.); (I.D.)
- Institute of Immunology and Physiology of the Ural Branch of the Russian Academy of Sciences, Ekaterinburg 620049, Russia
| | - Olga Solovyova
- Institute of Natural Sciences and Mathematics, Ural Federal University, Ekaterinburg 620075, Russia; (V.D.); (F.P.E.); (K.U.); (A.B.); (E.M.); (O.S.); (I.D.)
- Institute of Immunology and Physiology of the Ural Branch of the Russian Academy of Sciences, Ekaterinburg 620049, Russia
| | - Irina Danilova
- Institute of Natural Sciences and Mathematics, Ural Federal University, Ekaterinburg 620075, Russia; (V.D.); (F.P.E.); (K.U.); (A.B.); (E.M.); (O.S.); (I.D.)
- Institute of Immunology and Physiology of the Ural Branch of the Russian Academy of Sciences, Ekaterinburg 620049, Russia
| | - Elena Kovaleva
- Institute of Chemical Engineering, Ural Federal University, Ekaterinburg 620002, Russia; (S.A.); (V.S.); (E.K.)
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Zhuang Z, Sun L, Song X, Zhu H, Li L, Zhou X, Mi K. Trends and challenges of multi-drug resistance in childhood tuberculosis. Front Cell Infect Microbiol 2023; 13:1183590. [PMID: 37333849 PMCID: PMC10275406 DOI: 10.3389/fcimb.2023.1183590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 05/23/2023] [Indexed: 06/20/2023] Open
Abstract
Drug-resistant tuberculosis (DR-TB) in children is a growing global health concern, This review provides an overview of the current epidemiology of childhood TB and DR-TB, including prevalence, incidence, and mortality. We discuss the challenges in diagnosing TB and DR-TB in children and the limitations of current diagnostic tools. We summarize the challenges associated with treating multi-drug resistance TB in childhood, including limitations of current treatment options, drug adverse effects, prolonged regimens, and managing and monitoring during treatment. We highlight the urgent need for improved diagnosis and treatment of DR-TB in children. The treatment of children with multidrug-resistant tuberculosis will be expanded to include the evaluation of new drugs or new combinations of drugs. Basic research is needed to support the technological development of biomarkers to assess the phase of therapy, as well as the urgent need for improved diagnostic and treatment options.
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Affiliation(s)
- Zengfang Zhuang
- Chinese Academy of Sciences (CAS) Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
- Savaid Medical School, University of Chinese Academy of Sciences, Beijing, China
| | - Lin Sun
- Beijing Children’s Hospital, Capital Medical University, Beijing, China
| | - Xiaorui Song
- Henan International Joint Laboratory of Children’s Infectious Diseases, Children’s Hospital Affiliated to Zhengzhou University, Henan Children’s Hospital, Zhengzhou Children’s Hospital, Zhengzhou, China
| | - Hanzhao Zhu
- Chinese Academy of Sciences (CAS) Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
- Savaid Medical School, University of Chinese Academy of Sciences, Beijing, China
| | - Lianju Li
- Chinese Academy of Sciences (CAS) Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
- School of Basic Medicine, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Xintong Zhou
- Chinese Academy of Sciences (CAS) Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
| | - Kaixia Mi
- Chinese Academy of Sciences (CAS) Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
- Savaid Medical School, University of Chinese Academy of Sciences, Beijing, China
- Henan International Joint Laboratory of Children’s Infectious Diseases, Children’s Hospital Affiliated to Zhengzhou University, Henan Children’s Hospital, Zhengzhou Children’s Hospital, Zhengzhou, China
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5
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Yen NTH, Anh NK, Jayanti RP, Phat NK, Vu DH, Ghim JL, Ahn S, Shin JG, Oh JY, Phuoc Long N, Kim DH. Multimodal plasma metabolomics and lipidomics in elucidating metabolic perturbations in tuberculosis patients with concurrent type 2 diabetes. Biochimie 2023:S0300-9084(23)00086-X. [PMID: 37062470 DOI: 10.1016/j.biochi.2023.04.009] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 04/13/2023] [Accepted: 04/13/2023] [Indexed: 04/18/2023]
Abstract
Type 2 diabetes mellitus (DM) poses a major burden for the treatment and control of tuberculosis (TB). Characterization of the underlying metabolic perturbations in DM patients with TB infection would yield insights into the pathophysiology of TB-DM, thus potentially leading to improvements in TB treatment. In this study, a multimodal metabolomics and lipidomics workflow was applied to investigate plasma metabolic profiles of patients with TB and TB-DM. Significantly different biological processes and biomarkers in TB-DM vs. TB were identified using a data-driven, knowledge-based framework. Changes in metabolic and signaling pathways related to carbohydrate and amino acid metabolism were mainly captured by amide HILIC column metabolomics analysis, while perturbations in lipid metabolism were identified by the C18 metabolomics and lipidomics analysis. Compared to TB, TB-DM exhibited elevated levels of bile acids and molecules related to carbohydrate metabolism, as well as the depletion of glutamine, retinol, lysophosphatidylcholine, and phosphatidylcholine. Moreover, arachidonic acid metabolism was determined as a potential important factor in the interaction between TB and DM pathophysiology. In a correlation network of the significantly altered molecules, among the central nodes, chenodeoxycholic acid was robustly associated with TB and DM. Fatty acid (22:4) was a component of all significant modules. In conclusion, the integration of multimodal metabolomics and lipidomics provides a thorough picture of the metabolic changes associated with TB-DM. The results obtained from this comprehensive profiling of TB patients with DM advance the current understanding of DM comorbidity in TB infection and contribute to the development of more effective treatment.
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Affiliation(s)
- Nguyen Thi Hai Yen
- Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan, Republic of Korea; Center for Personalized Precision Medicine of Tuberculosis, Inje University College of Medicine, Busan, Republic of Korea
| | - Nguyen Ky Anh
- Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan, Republic of Korea; Center for Personalized Precision Medicine of Tuberculosis, Inje University College of Medicine, Busan, Republic of Korea
| | - Rannissa Puspita Jayanti
- Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan, Republic of Korea; Center for Personalized Precision Medicine of Tuberculosis, Inje University College of Medicine, Busan, Republic of Korea
| | - Nguyen Ky Phat
- Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan, Republic of Korea; Center for Personalized Precision Medicine of Tuberculosis, Inje University College of Medicine, Busan, Republic of Korea
| | - Dinh Hoa Vu
- The National Centre of Drug Information and Adverse Drug Reaction Monitoring, Hanoi University of Pharmacy, Hanoi, Viet Nam
| | - Jong-Lyul Ghim
- Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan, Republic of Korea; Department of Clinical Pharmacology, Inje University Busan Paik Hospital, Busan, Republic of Korea
| | - Sangzin Ahn
- Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan, Republic of Korea
| | - Jae-Gook Shin
- Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan, Republic of Korea; Center for Personalized Precision Medicine of Tuberculosis, Inje University College of Medicine, Busan, Republic of Korea; Department of Clinical Pharmacology, Inje University Busan Paik Hospital, Busan, Republic of Korea
| | - Jee Youn Oh
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Internal Medicine, Korea University Guro Hospital, Seoul, Republic of Korea
| | - Nguyen Phuoc Long
- Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan, Republic of Korea; Center for Personalized Precision Medicine of Tuberculosis, Inje University College of Medicine, Busan, Republic of Korea.
| | - Dong Hyun Kim
- Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan, Republic of Korea.
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6
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Fu J, Zhu F, Xu CJ, Li Y. Metabolomics meets systems immunology. EMBO Rep 2023; 24:e55747. [PMID: 36916532 PMCID: PMC10074123 DOI: 10.15252/embr.202255747] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 12/24/2022] [Accepted: 02/24/2023] [Indexed: 03/16/2023] Open
Abstract
Metabolic processes play a critical role in immune regulation. Metabolomics is the systematic analysis of small molecules (metabolites) in organisms or biological samples, providing an opportunity to comprehensively study interactions between metabolism and immunity in physiology and disease. Integrating metabolomics into systems immunology allows the exploration of the interactions of multilayered features in the biological system and the molecular regulatory mechanism of these features. Here, we provide an overview on recent technological developments of metabolomic applications in immunological research. To begin, two widely used metabolomics approaches are compared: targeted and untargeted metabolomics. Then, we provide a comprehensive overview of the analysis workflow and the computational tools available, including sample preparation, raw spectra data preprocessing, data processing, statistical analysis, and interpretation. Third, we describe how to integrate metabolomics with other omics approaches in immunological studies using available tools. Finally, we discuss new developments in metabolomics and its prospects for immunology research. This review provides guidance to researchers using metabolomics and multiomics in immunity research, thus facilitating the application of systems immunology to disease research.
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Affiliation(s)
- Jianbo Fu
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and Hannover Medical School (MHH), Hannover, Germany.,TWINCORE Centre for Experimental and Clinical Infection Research, a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany.,College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Feng Zhu
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Cheng-Jian Xu
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and Hannover Medical School (MHH), Hannover, Germany.,TWINCORE Centre for Experimental and Clinical Infection Research, a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany.,Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Yang Li
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and Hannover Medical School (MHH), Hannover, Germany.,TWINCORE Centre for Experimental and Clinical Infection Research, a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany.,Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, The Netherlands
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Yu Y, Jiang XX, Li JC. Biomarker discovery for tuberculosis using metabolomics. Front Mol Biosci 2023; 10:1099654. [PMID: 36891238 PMCID: PMC9986447 DOI: 10.3389/fmolb.2023.1099654] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 02/06/2023] [Indexed: 02/22/2023] Open
Abstract
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.
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Affiliation(s)
- Yi Yu
- Center for Analyses and Measurements, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou, China
| | - Xin-Xin Jiang
- Clinical Research Laboratory, Shaoxing Seventh People's Hospital, Shaoxing, China
| | - Ji-Cheng Li
- Clinical Research Laboratory, Shaoxing Seventh People's Hospital, Shaoxing, China.,Institute of Cell Biology, Zhejiang University Medical School, Hangzhou, China
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8
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Rawat BS, Kumar D, Soni V, Rosenn EH. Therapeutic Potentials of Immunometabolomic Modulations Induced by Tuberculosis Vaccination. Vaccines (Basel) 2022; 10:vaccines10122127. [PMID: 36560537 PMCID: PMC9781011 DOI: 10.3390/vaccines10122127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 12/03/2022] [Accepted: 12/08/2022] [Indexed: 12/15/2022] Open
Abstract
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.
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Affiliation(s)
- Bhupendra Singh Rawat
- Center for Immunity and Inflammation, Rutgers New Jersey Medical School, Newark, NJ 07103, USA
| | - Deepak Kumar
- Department of Zoology, University of Rajasthan, Jaipur 302004, Rajasthan, India
| | - Vijay Soni
- Division of Infectious Diseases, Weill Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA
- Correspondence:
| | - Eric H. Rosenn
- School of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel
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9
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Amalia F, Syamsunarno MRAA, Triatin RD, Fatimah SN, Chaidir L, Achmad TH. The Role of Amino Acids in Tuberculosis Infection: A Literature Review. Metabolites 2022; 12:933. [PMID: 36295834 PMCID: PMC9611225 DOI: 10.3390/metabo12100933] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 09/28/2022] [Accepted: 09/28/2022] [Indexed: 11/07/2022] Open
Abstract
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.
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Affiliation(s)
- Fiki Amalia
- Study Program of Medicine, Faculty of Medicine Universitas Padjadjaran, Bandung 40161, Jawa Barat, Indonesia
| | - Mas Rizky A. A. Syamsunarno
- Department of Biomedical Sciences, Faculty of Medicine Universitas Padjadjaran, Bandung 40161, Jawa Barat, Indonesia
- Center for Translational Biomarker Research, Universitas Padjadjaran, Bandung 40161, Jawa Barat, Indonesia
| | - Rima Destya Triatin
- Department of Biomedical Sciences, Faculty of Medicine Universitas Padjadjaran, Bandung 40161, Jawa Barat, Indonesia
| | - Siti Nur Fatimah
- Department of Public Health, Faculty of Medicine Universitas Padjadjaran, Bandung 40161, Jawa Barat, Indonesia
| | - Lidya Chaidir
- Department of Biomedical Sciences, Faculty of Medicine Universitas Padjadjaran, Bandung 40161, Jawa Barat, Indonesia
- Center for Translational Biomarker Research, Universitas Padjadjaran, Bandung 40161, Jawa Barat, Indonesia
| | - Tri Hanggono Achmad
- Department of Biomedical Sciences, Faculty of Medicine Universitas Padjadjaran, Bandung 40161, Jawa Barat, Indonesia
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