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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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2
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Wang C, Lou C, Yang Z, Shi J, Niu N. Plasma metabolomic analysis reveals the metabolic characteristics and potential diagnostic biomarkers of spinal tuberculosis. Heliyon 2024; 10:e27940. [PMID: 38571585 PMCID: PMC10987919 DOI: 10.1016/j.heliyon.2024.e27940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 02/16/2024] [Accepted: 03/08/2024] [Indexed: 04/05/2024] Open
Abstract
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.
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Affiliation(s)
- Chaoran Wang
- Department of Orthopedics, General Hospital of Ningxia Medical University, Yinchuan 750004, Ningxia, China
- School of Clinical Medicine, Ningxia Medical University, Yinchuan 750004, Ningxia, China
| | - Caili Lou
- School of Clinical Medicine, Ningxia Medical University, Yinchuan 750004, Ningxia, China
| | - Zongqiang Yang
- Department of Orthopedics, General Hospital of Ningxia Medical University, Yinchuan 750004, Ningxia, China
| | - Jiandang Shi
- Department of Orthopedics, General Hospital of Ningxia Medical University, Yinchuan 750004, Ningxia, China
| | - Ningkui Niu
- Department of Orthopedics, General Hospital of Ningxia Medical University, Yinchuan 750004, Ningxia, China
- Research Center for Prevention and Control of Bone and Joint Tuberculosis, General Hospital of Ningxia Medical University, Yinchuan 750004, Ningxia, China
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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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Ferreira AV, Alarcon-Barrera JC, Domínguez-Andrés J, Bulut Ö, Kilic G, Debisarun PA, Röring RJ, Özhan HN, Terschlüsen E, Ziogas A, Kostidis S, Mohammed Y, Matzaraki V, Renieris G, Giamarellos-Bourboulis EJ, Netea MG, Giera M. Fatty acid desaturation and lipoxygenase pathways support trained immunity. Nat Commun 2023; 14:7385. [PMID: 37968313 PMCID: PMC10651900 DOI: 10.1038/s41467-023-43315-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 11/06/2023] [Indexed: 11/17/2023] Open
Abstract
Infections and vaccines can induce enhanced long-term responses in innate immune cells, establishing an innate immunological memory termed trained immunity. Here, we show that monocytes with a trained immunity phenotype, due to exposure to the Bacillus Calmette-Guérin (BCG) vaccine, are characterized by an increased biosynthesis of different lipid mediators (LM) derived from long-chain polyunsaturated fatty acids (PUFA). Pharmacological and genetic approaches show that long-chain PUFA synthesis and lipoxygenase-derived LM are essential for the BCG-induced trained immunity responses of human monocytes. Furthermore, products of 12-lipoxygenase activity increase in monocytes of healthy individuals after BCG vaccination. Grasping the underscoring lipid metabolic pathways contributes to our understanding of trained immunity and may help to identify therapeutic tools and targets for the modulation of innate immune responses.
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Affiliation(s)
- Anaísa V Ferreira
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Nijmegen Medical Center, 6500HB, Nijmegen, The Netherlands.
- Instituto de Ciências Biomédicas Abel Salazar (ICBAS), Universidade do Porto, 4050-313, Porto, Portugal.
| | | | - Jorge Domínguez-Andrés
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Nijmegen Medical Center, 6500HB, Nijmegen, The Netherlands
| | - Özlem Bulut
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Nijmegen Medical Center, 6500HB, Nijmegen, The Netherlands
| | - Gizem Kilic
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Nijmegen Medical Center, 6500HB, Nijmegen, The Netherlands
| | - Priya A Debisarun
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Nijmegen Medical Center, 6500HB, Nijmegen, The Netherlands
| | - Rutger J Röring
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Nijmegen Medical Center, 6500HB, Nijmegen, The Netherlands
| | - Hatice N Özhan
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Nijmegen Medical Center, 6500HB, Nijmegen, The Netherlands
| | - Eva Terschlüsen
- Department of Medical Microbiology, Radboud University Medical Centre, 6500HB, Nijmegen, The Netherlands
| | - Athanasios Ziogas
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Nijmegen Medical Center, 6500HB, Nijmegen, The Netherlands
| | - Sarantos Kostidis
- Center for Proteomics and Metabolomics, Leiden University Medical Center, 2333ZA, Leiden, the Netherlands
| | - Yassene Mohammed
- Center for Proteomics and Metabolomics, Leiden University Medical Center, 2333ZA, Leiden, the Netherlands
| | - Vasiliki Matzaraki
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Nijmegen Medical Center, 6500HB, Nijmegen, The Netherlands
| | - George Renieris
- 4th Department of Internal Medicine, National and Kapodistrian University of Athens, Medical School, Athens, Greece
| | | | - Mihai G Netea
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Nijmegen Medical Center, 6500HB, Nijmegen, The Netherlands
- Department for Immunology and Metabolism, Life and Medical Sciences Institute (LIMES), University of Bonn, 53115, Bonn, Germany
| | - Martin Giera
- Center for Proteomics and Metabolomics, Leiden University Medical Center, 2333ZA, Leiden, the Netherlands.
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5
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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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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:metabo12100933. [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] [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
- Correspondence:
| | - 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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Long NP, Anh NK, Yen NTH, Phat NK, Park S, Thu VTA, Cho YS, Shin JG, Oh JY, Kim DH. Comprehensive lipid and lipid-related gene investigations of host immune responses to characterize metabolism-centric biomarkers for pulmonary tuberculosis. Sci Rep 2022; 12:13395. [PMID: 35927287 PMCID: PMC9352691 DOI: 10.1038/s41598-022-17521-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 07/26/2022] [Indexed: 12/04/2022] Open
Abstract
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.
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Affiliation(s)
- 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
| | - 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
| | - 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 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
| | - Seongoh Park
- School of Mathematics, Statistics and Data Science, Sungshin Women's University, Seoul, Republic of Korea
| | - Vo Thuy Anh Thu
- 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
| | - Yong-Soon Cho
- 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
| | - 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.
| | - Dong Hyun Kim
- Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan, Republic of Korea.
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8
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Magdalena D, Michal S, Marta S, Magdalena KP, Anna P, Magdalena G, Rafał S. Targeted metabolomics analysis of serum and Mycobacterium tuberculosis antigen-stimulated blood cultures of pediatric patients with active and latent tuberculosis. Sci Rep 2022; 12:4131. [PMID: 35260782 PMCID: PMC8904507 DOI: 10.1038/s41598-022-08201-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 03/03/2022] [Indexed: 12/28/2022] Open
Abstract
Profound tuberculosis (TB)-induced metabolic changes reflected in the blood metabolomic profile may provide an opportunity to identify specific markers of Mycobacterium tuberculosis infection. Using targeted liquid chromatography tandem mass spectrometry, we compared the levels of 30 small metabolites, including amino acids and derivatives, and small organic compounds in serum and M.tb antigen-stimulated whole blood cultures of active TB children, latent TB (LTBI) children, nonmycobacterial pneumonia (NMP) children, and healthy controls (HCs) to assess their potential as biomarkers of childhood TB. We found elevated levels of leucine and kynurenine combined with reduced concentrations of citrulline and glutamine in serum and blood cultures of TB and LTBI groups. LTBI status was additionally associated with a decrease in valine levels in blood cultures. The NMP metabolite profile was characterized by an increase in citrulline and glutamine and a decrease in leucine, kynurenine and valine concentrations. The highest discriminatory potential for identifying M.tb infection was observed for leucine detected in serum and kynurenine in stimulated blood cultures. The use of targeted metabolomics may reveal metabolic changes in M.tb-infected children, and the obtained results are a proof of principle of the usefulness of metabolites in the auxiliary diagnosis of TB in children.
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Affiliation(s)
- Druszczynska Magdalena
- Department of Immunology and Infectious Biology, Institute of Microbiology, Biotechnology and Immunology, Faculty of Biology and Environmental Protection, University of Lodz, Banacha 12/16, 90-237, Lodz, Poland.
| | - Seweryn Michal
- Biobank Lab, Department of Molecular Biophysics, Faculty of Biology and Environmental Protection, University of Lodz, Banacha 12/16, 90-237, Lodz, Poland
| | | | - Kowalewska-Pietrzak Magdalena
- Regional Specialized Hospital of Tuberculosis, Lung Diseases, and Rehabilitation in Lodz, Okolna 181, 91-520, Lodz, Poland
| | - Pankowska Anna
- Regional Specialized Hospital of Tuberculosis, Lung Diseases, and Rehabilitation in Lodz, Okolna 181, 91-520, Lodz, Poland
| | - Godkowicz Magdalena
- Department of Immunology and Infectious Biology, Institute of Microbiology, Biotechnology and Immunology, Faculty of Biology and Environmental Protection, University of Lodz, Banacha 12/16, 90-237, Lodz, Poland
| | - Szewczyk Rafał
- , Labexperts sp z o. o. Piekarnicza 5, 80-126, Gdansk, Poland
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9
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Ahamad N, Gupta S, Parashar D. Using Omics to Study Leprosy, Tuberculosis, and Other Mycobacterial Diseases. Front Cell Infect Microbiol 2022; 12:792617. [PMID: 35281437 PMCID: PMC8908319 DOI: 10.3389/fcimb.2022.792617] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Accepted: 02/01/2022] [Indexed: 12/12/2022] Open
Abstract
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.
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Affiliation(s)
- Naseem Ahamad
- Department of Oral and Maxillofacial Diagnostic Sciences, College of Dentistry, University of Florida, Gainesville, FL, United States
- *Correspondence: Naseem Ahamad,
| | - Saurabh Gupta
- Department of Biotechnology, GLA University, Mathura, India
| | - Deepak Parashar
- Department of Obstetrics and Gynecology, Medical College of Wisconsin, Milwaukee, WI, United States
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10
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Infection Biomarkers Based on Metabolomics. Metabolites 2022; 12:metabo12020092. [PMID: 35208167 PMCID: PMC8877834 DOI: 10.3390/metabo12020092] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 01/10/2022] [Accepted: 01/14/2022] [Indexed: 12/18/2022] Open
Abstract
Current infection biomarkers are highly limited since they have low capability to predict infection in the presence of confounding processes such as in non-infectious inflammatory processes, low capability to predict disease outcomes and have limited applications to guide and evaluate therapeutic regimes. Therefore, it is critical to discover and develop new and effective clinical infection biomarkers, especially applicable in patients at risk of developing severe illness and critically ill patients. Ideal biomarkers would effectively help physicians with better patient management, leading to a decrease of severe outcomes, personalize therapies, minimize antibiotics overuse and hospitalization time, and significantly improve patient survival. Metabolomics, by providing a direct insight into the functional metabolic outcome of an organism, presents a highly appealing strategy to discover these biomarkers. The present work reviews the desired main characteristics of infection biomarkers, the main metabolomics strategies to discover these biomarkers and the next steps for developing the area towards effective clinical biomarkers.
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11
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Shivakoti R, Newman JW, Hanna LE, Queiroz ATL, Borkowski K, Gupte AN, Paradkar M, Satyamurthi P, Kulkarni V, Selva M, Pradhan N, Shivakumar SVBY, Natarajan S, Karunaianantham R, Gupte N, Thiruvengadam K, Fiehn O, Bharadwaj R, Kagal A, Gaikwad S, Sangle S, Golub JE, Andrade BB, Mave V, Gupta A, Padmapriyadarsini C. Host lipidome and tuberculosis treatment failure. Eur Respir J 2022; 59:2004532. [PMID: 34375300 PMCID: PMC9625841 DOI: 10.1183/13993003.04532-2020] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 05/24/2021] [Indexed: 01/09/2023]
Abstract
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.
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Affiliation(s)
- Rupak Shivakoti
- Dept of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Dept of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
| | - John W Newman
- Obesity and Metabolism Research Unit, Western Human Nutrition Research Center, Agricultural Research Service, United States Department of Agriculture, Davis, CA, USA
- Dept of Nutrition, University of California, Davis, CA, USA
- West Coast Metabolomics Center, University of California, Davis, CA, USA
| | | | - Artur T L Queiroz
- Instituto Goncalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
- Multinational Organization Network Sponsoring Translational and Epidemiological Research, Salvador, Brazil
| | - Kamil Borkowski
- West Coast Metabolomics Center, University of California, Davis, CA, USA
| | - Akshay N Gupte
- Dept of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Mandar Paradkar
- Byramjee-Jeejeebhoy Medical College-Johns Hopkins University Clinical Research Site, Pune, India
| | | | - Vandana Kulkarni
- Byramjee-Jeejeebhoy Medical College-Johns Hopkins University Clinical Research Site, Pune, India
| | - Murugesh Selva
- National Institute for Research in Tuberculosis, Chennai, India
| | - Neeta Pradhan
- Byramjee-Jeejeebhoy Medical College-Johns Hopkins University Clinical Research Site, Pune, India
| | | | | | | | - Nikhil Gupte
- Dept of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Byramjee-Jeejeebhoy Medical College-Johns Hopkins University Clinical Research Site, Pune, India
| | | | - Oliver Fiehn
- West Coast Metabolomics Center, University of California, Davis, CA, USA
| | - Renu Bharadwaj
- Byramjee-Jeejeebhoy Government Medical College, Pune, India
| | - Anju Kagal
- Byramjee-Jeejeebhoy Government Medical College, Pune, India
| | - Sanjay Gaikwad
- Byramjee-Jeejeebhoy Government Medical College, Pune, India
| | | | - Jonathan E Golub
- Dept of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Bruno B Andrade
- Instituto Goncalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
- Multinational Organization Network Sponsoring Translational and Epidemiological Research, Salvador, Brazil
- Faculdade de Medicina, Universidade Federal da Bahia, Salvador, Brazil
- Curso de Medicina, Faculdade de Tecnologia e Ciências, Salvador, Brazil
- Curso de Medicina, Universidade Salvador (UNIFACS), Laureate International Universities, Salvador, Brazil
- Escola Bahiana de Medicina e Saúde Pública (EBMSP), Salvador, Brazil
| | - Vidya Mave
- Dept of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Byramjee-Jeejeebhoy Medical College-Johns Hopkins University Clinical Research Site, Pune, India
| | - Amita Gupta
- Dept of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Byramjee-Jeejeebhoy Medical College-Johns Hopkins University Clinical Research Site, Pune, India
- Equal contribution
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12
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TCA cycle remodeling drives proinflammatory signaling in humans with pulmonary tuberculosis. PLoS Pathog 2021; 17:e1009941. [PMID: 34559866 PMCID: PMC8494353 DOI: 10.1371/journal.ppat.1009941] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 10/06/2021] [Accepted: 09/03/2021] [Indexed: 11/19/2022] Open
Abstract
The metabolic signaling pathways that drive pathologic tissue inflammation and damage in humans with pulmonary tuberculosis (TB) are not well understood. Using combined methods in plasma high-resolution metabolomics, lipidomics and cytokine profiling from a multicohort study of humans with pulmonary TB disease, we discovered that IL-1β-mediated inflammatory signaling was closely associated with TCA cycle remodeling, characterized by accumulation of the proinflammatory metabolite succinate and decreased concentrations of the anti-inflammatory metabolite itaconate. This inflammatory metabolic response was particularly active in persons with multidrug-resistant (MDR)-TB that received at least 2 months of ineffective treatment and was only reversed after 1 year of appropriate anti-TB chemotherapy. Both succinate and IL-1β were significantly associated with proinflammatory lipid signaling, including increases in the products of phospholipase A2, increased arachidonic acid formation, and metabolism of arachidonic acid to proinflammatory eicosanoids. Together, these results indicate that decreased itaconate and accumulation of succinate and other TCA cycle intermediates is associated with IL-1β-mediated proinflammatory eicosanoid signaling in pulmonary TB disease. These findings support host metabolic remodeling as a key driver of pathologic inflammation in human TB disease. Pulmonary tuberculosis (TB) often results in pathologic lung inflammation that causes tissue damage and does not control bacterial replication. This impairs the host response to antibiotic treatment and can result in long term deficits in lung function. Currently, the role of host metabolism in regulating the inflammatory response in TB disease is not well understood. Here, we use detailed immunometabolic phenotyping to show that metabolic remodeling of the tricarboxylic acid (TCA) cycle is closely associated with pathologic inflammatory signaling in humans with TB disease. Accumulation of TCA cycle intermediates in plasma, including the proinflammatory metabolite succinate, as well as decreased concentrations of the anti-inflammatory metabolite itaconate, were associated with increases in IL-1β and upregulation of proinflammatory lipid signaling cascades. This inflammatory network was upregulated following delays in appropriate anti-TB treatment and was associated with prolonged time to sputum culture clearance of Mycobacterium tuberculosis. Our study provides new insights into the metabolic reprograming that leads to pathologic inflammation in humans with pulmonary TB.
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13
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Jøntvedt Jørgensen M, Nore KG, Aass HCD, Layre E, Nigou J, Mortensen R, Tasken K, Kvale D, Jenum S, Tonby K, Dyrhol-Riise AM. Plasma LOX-Products and Monocyte Signaling Is Reduced by Adjunctive Cyclooxygenase-2 Inhibitor in a Phase I Clinical Trial of Tuberculosis Patients. Front Cell Infect Microbiol 2021; 11:669623. [PMID: 34307194 PMCID: PMC8299478 DOI: 10.3389/fcimb.2021.669623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Accepted: 06/21/2021] [Indexed: 11/22/2022] Open
Abstract
Introduction Eicosanoids and intracellular signaling pathways are potential targets for host-directed therapy (HDT) in tuberculosis (TB). We have explored the effect of cyclooxygenase 2 inhibitor (COX-2i) treatment on eicosanoid levels and signaling pathways in monocytes. Methods Peripheral blood mononuclear cells isolated from TB patients included in a randomized phase I clinical trial of standard TB treatment with (n=21) or without (n=18) adjunctive COX-2i (etoricoxib) were analyzed at baseline, day 14 and day 56. Plasma eicosanoids were analyzed by ELISA and liquid chromatography-mass spectrometry (LC-MS), plasma cytokines by multiplex, and monocyte signaling by phospho-flow with a defined set of phospho-specific antibodies. Results Lipoxygenase (LOX)-derived products (LXA4 and 12-HETE) and pro-inflammatory cytokines were associated with TB disease severity and were reduced during TB therapy, possibly accelerated by adjunctive COX-2i. Phosphorylation of p38 MAPK, NFkB, Erk1/2, and Akt in monocytes as well as plasma levels of MIG/CXCL9 and procalcitonin were reduced in the COX-2i group compared to controls. Conclusion COX-2i may reduce excess inflammation in TB via the LOX-pathway in addition to modulation of phosphorylation patterns in monocytes. Immunomodulatory effects of adjunctive COX-2i in TB should be further investigated before recommended for use as a HDT strategy.
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Affiliation(s)
- Marthe Jøntvedt Jørgensen
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Infectious Diseases, Oslo University Hospital, Oslo, Norway
| | - Kristin G Nore
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | | | - Emilie Layre
- Institut de Pharmacologie et de Biologie Structurale, Université de Toulouse, CNRS, Université Paul Sabatier, Toulouse, France
| | - Jérôme Nigou
- Institut de Pharmacologie et de Biologie Structurale, Université de Toulouse, CNRS, Université Paul Sabatier, Toulouse, France
| | - Rasmus Mortensen
- Department of Infectious Disease Immunology, Statens Serum Institut, Copenhagen, Denmark
| | - Kjetil Tasken
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Deparment of Cancer Immunology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Dag Kvale
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Synne Jenum
- Department of Infectious Diseases, Oslo University Hospital, Oslo, Norway
| | - Kristian Tonby
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Infectious Diseases, Oslo University Hospital, Oslo, Norway
| | - Anne Ma Dyrhol-Riise
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Infectious Diseases, Oslo University Hospital, Oslo, Norway
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14
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Broza YY, Haick H. Biodiagnostics in an era of global pandemics-From biosensing materials to data management. VIEW 2021; 3:20200164. [PMID: 34766159 PMCID: PMC8441813 DOI: 10.1002/viw.20200164] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2020] [Revised: 03/10/2021] [Accepted: 04/12/2021] [Indexed: 12/15/2022] Open
Abstract
The novel corona virus SARS‐CoV‐2 (COVID‐19) has exposed the world to challenges never before seen in fast diagnostics, monitoring, and prevention of the outbreak. As a result, different approaches for fast diagnostic and screening are made and yet to find the ideal way. The current mini‐review provides and examines evidence‐based innovative and rapid chemical sensing and related biodiagnostic solutions to deal with infectious disease and related pandemic emergencies, which could offer the best possible care for the general population and improve the approachability of the pandemic information, insights, and surrounding contexts. The review discusses how integration of sensing devices with big data analysis, artificial Intelligence or machine learning, and clinical decision support system, could improve the accuracy of the recorded patterns of the disease conditions within an ocean of information. At the end, the mini‐review provides a prospective on the requirements to improve our coping of the pandemic‐related biodiagnostics as well as future opportunities.
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Affiliation(s)
- Yoav Y Broza
- Department of Chemical Engineering and Russell Berrie Nanotechnology Institute Technion-Israel Institute of Technology Haifa Israel
| | - Hossam Haick
- Department of Chemical Engineering and Russell Berrie Nanotechnology Institute Technion-Israel Institute of Technology Haifa Israel
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15
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Krishnan S, Queiroz ATL, Gupta A, Gupte N, Bisson GP, Kumwenda J, Naidoo K, Mohapi L, Mave V, Mngqibisa R, Lama JR, Hosseinipour MC, Andrade BB, Karakousis PC. Integrative Multi-Omics Reveals Serum Markers of Tuberculosis in Advanced HIV. Front Immunol 2021; 12:676980. [PMID: 34168648 PMCID: PMC8217878 DOI: 10.3389/fimmu.2021.676980] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Accepted: 05/13/2021] [Indexed: 11/13/2022] Open
Abstract
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.
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Affiliation(s)
- Sonya Krishnan
- Center for Clinical Global Health Education and Center for Tuberculosis Research, Division of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Artur T. L. Queiroz
- Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
- Multinational Organization Network Sponsoring Translational and Epidemiological Research (MONSTER) Initiative, Salvador, Brazil
| | - Amita Gupta
- Center for Clinical Global Health Education and Center for Tuberculosis Research, Division of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Byramjee Jeejeebhoy Government Medical College-Johns Hopkins University Clinical Research Site, Pune, India
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Nikhil Gupte
- Center for Clinical Global Health Education and Center for Tuberculosis Research, Division of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Byramjee Jeejeebhoy Government Medical College-Johns Hopkins University Clinical Research Site, Pune, India
| | - Gregory P. Bisson
- Department of Medicine, Division of Infectious Diseases, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | | | - Kogieleum Naidoo
- Centre for the AIDS Programme of Research in South Africa, Nelson R Mandela School of Medicine, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
- South African Medical Research Council-CAPRISA HIV-TB Pathogenesis and Treatment Research Unit, Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban, South Africa
| | - Lerato Mohapi
- Soweto ACTG CRS, Perinatal HIV Research Unit, University of the Witwatersrand, Johannesburg, South Africa
| | - Vidya Mave
- Byramjee Jeejeebhoy Government Medical College-Johns Hopkins University Clinical Research Site, Pune, India
| | - Rosie Mngqibisa
- Durban International Clinical Research Site, Enhancing Care Foundation, Durban, South Africa
| | | | - Mina C. Hosseinipour
- University of North Carolina Project-Malawi, Lilongwe, Malawi
- Division of Infectious Diseases, Department of Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, United States
| | - Bruno B. Andrade
- Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
- Multinational Organization Network Sponsoring Translational and Epidemiological Research (MONSTER) Initiative, Salvador, Brazil
- Curso de Medicina, Faculdade de Tecnologia e Ciências (FTC), Salvador, Brazil
- Curso de Medicina, Escola Bahiana de Medicina e Saúde Pública (EBMSP), Salvador, Brazil
| | - Petros C. Karakousis
- Center for Clinical Global Health Education and Center for Tuberculosis Research, Division of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
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16
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Metabolomic profiling of microbial disease etiology in community-acquired pneumonia. PLoS One 2021; 16:e0252378. [PMID: 34086721 PMCID: PMC8177549 DOI: 10.1371/journal.pone.0252378] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 05/15/2021] [Indexed: 11/30/2022] Open
Abstract
Diagnosis of microbial disease etiology in community-acquired pneumonia (CAP) remains challenging. We undertook a large-scale metabolomics study of serum samples in hospitalized CAP patients to determine if host-response associated metabolites can enable diagnosis of microbial etiology, with a specific focus on discrimination between the major CAP pathogen groups S. pneumoniae, atypical bacteria, and respiratory viruses. Targeted metabolomic profiling of serum samples was performed for three groups of hospitalized CAP patients with confirmed microbial etiologies: S. pneumoniae (n = 48), atypical bacteria (n = 47), or viral infections (n = 30). A wide range of 347 metabolites was targeted, including amines, acylcarnitines, organic acids, and lipids. Single discriminating metabolites were selected using Student’s T-test and their predictive performance was analyzed using logistic regression. Elastic net regression models were employed to discover metabolite signatures with predictive value for discrimination between pathogen groups. Metabolites to discriminate S. pneumoniae or viral pathogens from the other groups showed poor predictive capability, whereas discrimination of atypical pathogens from the other groups was found to be possible. Classification of atypical pathogens using elastic net regression models was associated with a predictive performance of 61% sensitivity, 86% specificity, and an AUC of 0.81. Targeted profiling of the host metabolic response revealed metabolites that can support diagnosis of microbial etiology in CAP patients with atypical bacterial pathogens compared to patients with S. pneumoniae or viral infections.
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17
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Park JH, Shim D, Kim KES, Lee W, Shin SJ. Understanding Metabolic Regulation Between Host and Pathogens: New Opportunities for the Development of Improved Therapeutic Strategies Against Mycobacterium tuberculosis Infection. Front Cell Infect Microbiol 2021; 11:635335. [PMID: 33796480 PMCID: PMC8007978 DOI: 10.3389/fcimb.2021.635335] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 03/01/2021] [Indexed: 12/21/2022] Open
Abstract
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.
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Affiliation(s)
- Ji-Hae Park
- Department of Microbiology, Institute for Immunology and Immunological Diseases, Brain Korea 21 Project for Graduate School of Medical Science, Yonsei University College of Medicine, Seoul, South Korea
| | - Dahee Shim
- Department of Microbiology, Institute for Immunology and Immunological Diseases, Brain Korea 21 Project for Graduate School of Medical Science, Yonsei University College of Medicine, Seoul, South Korea
| | - Keu Eun San Kim
- Department of Microbiology, Institute for Immunology and Immunological Diseases, Brain Korea 21 Project for Graduate School of Medical Science, Yonsei University College of Medicine, Seoul, South Korea
| | - Wonsik Lee
- School of Pharmacy, Sungkyunkwan University, Suwon, South Korea
| | - Sung Jae Shin
- Department of Microbiology, Institute for Immunology and Immunological Diseases, Brain Korea 21 Project for Graduate School of Medical Science, Yonsei University College of Medicine, Seoul, South Korea
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18
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Sivakumaran D, Ritz C, Gjøen JE, Vaz M, Selvam S, Ottenhoff THM, Doherty TM, Jenum S, Grewal HMS. Host Blood RNA Transcript and Protein Signatures for Sputum-Independent Diagnostics of Tuberculosis in Adults. Front Immunol 2021; 11:626049. [PMID: 33613569 PMCID: PMC7891042 DOI: 10.3389/fimmu.2020.626049] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 12/21/2020] [Indexed: 12/21/2022] Open
Abstract
To achieve the ambitious targets for tuberculosis (TB) prevention, care, and control stated by the End TB Strategy, new health care strategies, diagnostic tools are warranted. Host-derived biosignatures are explored for their TB diagnostic potential in accordance with the WHO target product profiles (TPPs) for point-of-care (POC) testing. We aimed to identify sputum-independent TB diagnostic signatures in newly diagnosed adult pulmonary-TB (PTB) patients recruited in the context of a prospective household contact cohort study conducted in Andhra Pradesh, India. Whole-blood mRNA samples from 158 subjects (PTB, n = 109; age-matched household controls, n = 49) were examined by dual-color Reverse-Transcriptase Multiplex Ligation-dependent Probe-Amplification (dcRT-MLPA) for the expression of 198 pre-defined genes and a Mesoscale discovery assay for the concentration of 18 cytokines/chemokines in TB-antigen stimulated QuantiFERON supernatants. To identify signatures, we applied a two-step approach; in the first step, univariate filtering was used to identify and shortlist potentially predictive biomarkers; this step may be seen as removing redundant biomarkers. In the second step, a logistic regression approach was used such that group membership (PTB vs. household controls) became the binary response in a Lasso regression model. We identified an 11-gene signature that distinguished PTB from household controls with AUCs of ≥0.98 (95% CIs: 0.94–1.00), and a 4-protein signature (IFNγ, GMCSF, IL7 and IL15) that differentiated PTB from household controls with AUCs of ≥0.87 (95% CIs: 0.75–1.00), in our discovery cohort. Subsequently, we evaluated the performance of the 11-gene signature in two external validation data sets viz, an independent cohort at the Glenfield Hospital, University Hospitals of Leicester NHS Trust, Leicester, UK (GSE107994 data set), and the Catalysis treatment response cohort (GSE89403 data set) from South Africa. The 11-gene signature validated and distinguished PTB from healthy and asymptomatic M. tuberculosis infected household controls in the GSE107994 data set, with an AUC of 0.95 (95% CI: 0.91–0.98) and 0.94 (95% CI: 0.89–0.98). More interestingly in the GSE89403 data set, the 11-gene signature distinguished PTB from household controls and patients with other lung diseases with an AUC of 0.93 (95% CI: 0.87–0.99) and 0.73 (95% CI: 0.56–0.89). These criteria meet the WHO TTP benchmarks for a non–sputum-based triage test for TB diagnosis. We suggest that further validation is required before clinical implementation of the 11-gene signature we have identified markers will be possible.
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Affiliation(s)
- Dhanasekaran Sivakumaran
- Department of Clinical Science, Faculty of Medicine, University of Bergen, Bergen, Norway.,Department of Microbiology, Haukeland University Hospital, University of Bergen, Bergen, Norway
| | - Christian Ritz
- Department of Clinical Science, Faculty of Medicine, University of Bergen, Bergen, Norway.,Department of Nutrition, Exercise and Sports, University of Copenhagen, Copenhagen, Denmark
| | - John Espen Gjøen
- Department of Paediatrics, Haukeland University Hospital, Bergen, Norway
| | - Mario Vaz
- Department of Physiology, St. John's Medical College and Division of Health and Humanities, St. John's Research Institute, Bangalore, India
| | - Sumithra Selvam
- Division of Infectious Diseases, St. John's Research Institute, Bangalore, India
| | - Tom H M Ottenhoff
- Department of Infectious Diseases, Leiden University Medical Center, Leiden, Netherlands
| | | | - Synne Jenum
- Department of Infectious Diseases, Oslo University Hospital, Oslo, Norway
| | - Harleen M S Grewal
- Department of Clinical Science, Faculty of Medicine, University of Bergen, Bergen, Norway.,Department of Microbiology, Haukeland University Hospital, University of Bergen, Bergen, Norway
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19
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Kanabalan RD, Lee LJ, Lee TY, Chong PP, Hassan L, Ismail R, Chin VK. Human tuberculosis and Mycobacterium tuberculosis complex: A review on genetic diversity, pathogenesis and omics approaches in host biomarkers discovery. Microbiol Res 2021; 246:126674. [PMID: 33549960 DOI: 10.1016/j.micres.2020.126674] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 12/09/2020] [Accepted: 12/16/2020] [Indexed: 12/16/2022]
Abstract
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.
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Affiliation(s)
- Renuga Devi Kanabalan
- Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Jalan Yaacob Latiff, Bandar Tun Razak, Kuala Lumpur, 56000, Malaysia
| | - Le Jie Lee
- Prima Nexus Sdn. Bhd., Menara CIMB, Jalan Stesen Sentral 2, Kuala Lumpur, Malaysia
| | - Tze Yan Lee
- Perdana University School of Liberal Arts, Science and Technology (PUScLST), Suite 9.2, 9th Floor, Wisma Chase Perdana, Changkat Semantan Damansara Heights, Kuala Lumpur, 50490, Malaysia
| | - Pei Pei Chong
- School of Biosciences, Faculty of Health and Medical Sciences, Taylor's University Lakeside Campus, Subang Jaya, 47500, Malaysia
| | - Latiffah Hassan
- Department of Veterinary Laboratory Diagnostics, Faculty of Veterinary Medicine, Universiti Putra Malaysia, Serdang, Selangor, 43400 UPM, Malaysia
| | - Rosnah Ismail
- Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Jalan Yaacob Latiff, Bandar Tun Razak, Kuala Lumpur, 56000, Malaysia.
| | - Voon Kin Chin
- Department of Medical Microbiology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, 43400 UPM, Malaysia; Integrative Pharmacogenomics Institute (iPROMISE), Universiti Teknologi MARA, Puncak Alam Campus, Bandar Puncak Alam, Selangor, 42300, Malaysia.
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20
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Rytter H, Jamet A, Coureuil M, Charbit A, Ramond E. Which Current and Novel Diagnostic Avenues for Bacterial Respiratory Diseases? Front Microbiol 2020; 11:616971. [PMID: 33362754 PMCID: PMC7758241 DOI: 10.3389/fmicb.2020.616971] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Accepted: 11/24/2020] [Indexed: 12/24/2022] Open
Abstract
Bacterial acute pneumonia is responsible for an extremely large burden of death worldwide and diagnosis is paramount in the management of patients. While multidrug-resistant bacteria is one of the biggest health threats in the coming decades, clinicians urgently need access to novel diagnostic technologies. In this review, we will first present the already existing and largely used techniques that allow identifying pathogen-associated pneumonia. Then, we will discuss the latest and most promising technological advances that are based on connected technologies (artificial intelligence-based and Omics-based) or rapid tests, to improve the management of lung infections caused by pathogenic bacteria. We also aim to highlight the mutual benefits of fundamental and clinical studies for a better understanding of lung infections and their more efficient diagnostic management.
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Affiliation(s)
- Héloïse Rytter
- Université de Paris, Paris, France.,INSERM U1151, Institut Necker-Enfants Malades. Team 7, Pathogenesis of Systemic Infections, Paris, France.,CNRS UMR 8253, Paris, France
| | - Anne Jamet
- Université de Paris, Paris, France.,INSERM U1151, Institut Necker-Enfants Malades. Team 7, Pathogenesis of Systemic Infections, Paris, France.,CNRS UMR 8253, Paris, France.,Department of Clinical Microbiology, Necker Enfants-Malades Hospital, AP-HP, Centre Université de Paris, Paris, France
| | - Mathieu Coureuil
- Université de Paris, Paris, France.,INSERM U1151, Institut Necker-Enfants Malades. Team 7, Pathogenesis of Systemic Infections, Paris, France.,CNRS UMR 8253, Paris, France
| | - Alain Charbit
- Université de Paris, Paris, France.,INSERM U1151, Institut Necker-Enfants Malades. Team 7, Pathogenesis of Systemic Infections, Paris, France.,CNRS UMR 8253, Paris, France
| | - Elodie Ramond
- Université de Paris, Paris, France.,INSERM U1151, Institut Necker-Enfants Malades. Team 7, Pathogenesis of Systemic Infections, Paris, France.,CNRS UMR 8253, Paris, France
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21
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Integration of metabolomics and transcriptomics reveals novel biomarkers in the blood for tuberculosis diagnosis in children. Sci Rep 2020; 10:19527. [PMID: 33177551 PMCID: PMC7658223 DOI: 10.1038/s41598-020-75513-8] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 10/13/2020] [Indexed: 01/11/2023] Open
Abstract
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.
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22
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Pediatric Tuberculosis: The Impact of "Omics" on Diagnostics Development. Int J Mol Sci 2020; 21:ijms21196979. [PMID: 32977381 PMCID: PMC7582311 DOI: 10.3390/ijms21196979] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 09/15/2020] [Accepted: 09/17/2020] [Indexed: 02/07/2023] Open
Abstract
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.
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23
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Tuberculosis causes highly conserved metabolic changes in human patients, mycobacteria-infected mice and zebrafish larvae. Sci Rep 2020; 10:11635. [PMID: 32669636 PMCID: PMC7363909 DOI: 10.1038/s41598-020-68443-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Accepted: 06/23/2020] [Indexed: 12/20/2022] Open
Abstract
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.
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24
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Andreas NJ, Basu Roy R, Gomez-Romero M, Horneffer-van der Sluis V, Lewis MR, Camuzeaux SSM, Jiménez B, Posma JM, Tientcheu L, Egere U, Sillah A, Togun T, Holmes E, Kampmann B. Performance of metabonomic serum analysis for diagnostics in paediatric tuberculosis. Sci Rep 2020; 10:7302. [PMID: 32350385 PMCID: PMC7190829 DOI: 10.1038/s41598-020-64413-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2018] [Accepted: 03/13/2020] [Indexed: 12/31/2022] Open
Abstract
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.
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Affiliation(s)
- Nicholas J Andreas
- Centre for International Child Health, Department of Paediatrics, Imperial College London, St. Mary's Hospital, Praed Street, London, W2 1NY, United Kingdom
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, United Kingdom
| | - Robindra Basu Roy
- Centre for International Child Health, Department of Paediatrics, Imperial College London, St. Mary's Hospital, Praed Street, London, W2 1NY, United Kingdom
- MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine, Vaccines and Immunity Theme, Atlantic Road, Fajara, The Gambia
- The Vaccine Centre, Department of Clinical Research, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, United Kingdom
| | - Maria Gomez-Romero
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, United Kingdom
- MRC-NIHR National Phenome Centre, Department of Surgery and Cancer, Imperial College London, IRDB Building, Du Cane Road, London, W12 0NN, United Kingdom
- Clinical Phenotyping Centre, Department of Surgery and Cancer, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, United Kingdom
| | - Verena Horneffer-van der Sluis
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, United Kingdom
- MRC-NIHR National Phenome Centre, Department of Surgery and Cancer, Imperial College London, IRDB Building, Du Cane Road, London, W12 0NN, United Kingdom
| | - Matthew R Lewis
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, United Kingdom
- MRC-NIHR National Phenome Centre, Department of Surgery and Cancer, Imperial College London, IRDB Building, Du Cane Road, London, W12 0NN, United Kingdom
- Clinical Phenotyping Centre, Department of Surgery and Cancer, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, United Kingdom
| | - Stephane S M Camuzeaux
- MRC-NIHR National Phenome Centre, Department of Surgery and Cancer, Imperial College London, IRDB Building, Du Cane Road, London, W12 0NN, United Kingdom
| | - Beatriz Jiménez
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, United Kingdom
- MRC-NIHR National Phenome Centre, Department of Surgery and Cancer, Imperial College London, IRDB Building, Du Cane Road, London, W12 0NN, United Kingdom
- Clinical Phenotyping Centre, Department of Surgery and Cancer, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, United Kingdom
| | - Joram M Posma
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, United Kingdom
| | - Leopold Tientcheu
- MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine, Vaccines and Immunity Theme, Atlantic Road, Fajara, The Gambia
| | - Uzochukwu Egere
- MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine, Vaccines and Immunity Theme, Atlantic Road, Fajara, The Gambia
| | - Abdou Sillah
- MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine, Vaccines and Immunity Theme, Atlantic Road, Fajara, The Gambia
| | - Toyin Togun
- MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine, Vaccines and Immunity Theme, Atlantic Road, Fajara, The Gambia
- The Vaccine Centre, Department of Clinical Research, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, United Kingdom
| | - Elaine Holmes
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, United Kingdom
| | - Beate Kampmann
- Centre for International Child Health, Department of Paediatrics, Imperial College London, St. Mary's Hospital, Praed Street, London, W2 1NY, United Kingdom.
- MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine, Vaccines and Immunity Theme, Atlantic Road, Fajara, The Gambia.
- The Vaccine Centre, Department of Clinical Research, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, United Kingdom.
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25
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Identification of serum biomarkers for active pulmonary tuberculosis using a targeted metabolomics approach. Sci Rep 2020; 10:3825. [PMID: 32123207 PMCID: PMC7052258 DOI: 10.1038/s41598-020-60669-0] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Accepted: 02/13/2020] [Indexed: 12/13/2022] Open
Abstract
Although tuberculosis (TB) is a severe health problem worldwide, the current diagnostic methods are far from optimal. Metabolomics is increasingly being used in the study of infectious diseases. We performed metabolome profiling to identify potential biomarkers in patients with active TB. Serum samples from 21 patients with active pulmonary TB, 20 subjects with latent TB infection (LTBI), and 28 healthy controls were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) followed by multivariate and univariate analyses. Metabolic profiles indicated higher serum levels of glutamate, sulfoxy methionine, and aspartate and lower serum levels of glutamine, methionine, and asparagine in active TB patients than in LTBI subjects or healthy controls. The ratios between metabolically related partners (glutamate/glutamine, sulfoxy methionine/methionine, and aspartate/asparagine) were also elevated in the active TB group. There was no significant difference in the serum concentration of these metabolites according to the disease extent or risk of relapse in active TB patients. Novel serum biomarkers such as glutamate, sulfoxy methionine, aspartate, glutamine, methionine, and asparagine are potentially useful for adjunctive, rapid, and noninvasive pulmonary TB diagnosis.
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26
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Plasma metabolites Xanthine, 4-Pyridoxate, and d-glutamic acid as novel potential biomarkers for pulmonary tuberculosis. Clin Chim Acta 2019; 498:135-142. [DOI: 10.1016/j.cca.2019.08.017] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2019] [Revised: 08/18/2019] [Accepted: 08/19/2019] [Indexed: 12/14/2022]
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27
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NMR metabolome of Borrelia burgdorferi in vitro and in vivo in mice. Sci Rep 2019; 9:8049. [PMID: 31142787 PMCID: PMC6541645 DOI: 10.1038/s41598-019-44540-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2018] [Accepted: 05/20/2019] [Indexed: 12/25/2022] Open
Abstract
Lyme borreliosis (LB), caused by bacteria of the Borrelia burgdorferi sensu lato (Borrelia) species, is the most common tick-borne infection in the northern hemisphere. LB diagnostics is based on clinical evaluation of the patient and on laboratory testing, where the main method is the detection of Borrelia specific antibodies in patient samples. There are, however, shortcomings in the current serology based LB diagnostics, especially its inability to differentiate ongoing infection from a previously treated one. Identification of specific biomarkers of diseases is a growing application of metabolomics. One of the main methods of metabolomics is nuclear magnetic resonance (NMR) spectroscopy. In the present study, our aim was to analyze whether Borrelia growth in vitro and infection in vivo in mice causes specific metabolite differences, and whether NMR can be used to detect them. For this purpose, we performed NMR analyses of in vitro culture medium samples, and of serum and urine samples of Borrelia infected and control mice. The results show, that there were significant differences in the concentrations of several amino acids, energy metabolites and aromatic compounds between Borrelia culture and control media, and between infected and control mouse serum and urine samples. For example, the concentration of L-phenylalanine increases in the Borrelia growth medium and in serum of infected mice, whereas the concentrations of allantoin and trigonelline decrease in the urine of infected mice. Therefore, we conclude that Borrelia infection causes measurable metabolome differences in vitro and in Borrelia infected mouse serum and urine samples, and that these can be detected with NMR.
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28
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Metabolite Profiling: A Tool for the Biochemical Characterisation of Mycobacterium sp. Microorganisms 2019; 7:microorganisms7050148. [PMID: 31130621 PMCID: PMC6560386 DOI: 10.3390/microorganisms7050148] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Revised: 05/13/2019] [Accepted: 05/25/2019] [Indexed: 12/19/2022] Open
Abstract
Over the last decades, the prevalence of drug-resistance in Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis, has increased. These findings have rekindled interest in elucidating the unique adaptive molecular and biochemistry physiology of Mycobacterium. The use of metabolite profiling independently or in combination with other levels of "-omic" analyses has proven an effective approach to elucidate key physiological/biochemical mechanisms associated with Mtb throughout infection. The following review discusses the use of metabolite profiling in the study of tuberculosis, future approaches, and the technical and logistical limitations of the methodology.
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29
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Kartsova LA, Solov’eva SA. Application of Chromatographic and Electrophoretic Techniques to Metabolomic Studies. JOURNAL OF ANALYTICAL CHEMISTRY 2019. [DOI: 10.1134/s1061934819040051] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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30
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Poeta P, Silva V, Guedes A, Eduardo Pereira J, Cláudia Coelho A, Igrejas G. Tuberculosis in the 21th century: Current status of diagnostic methods. Exp Lung Res 2019; 44:352-360. [PMID: 30663432 DOI: 10.1080/01902148.2018.1545880] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
Tuberculosis is an infectious bacterial disease with a high mortality rate worldwide constituting a serious public health problem. The diagnostic methods commonly used by health professionals are slow and expensive and the results may take about sixty days which will cause a delay in administrating the most proper treatment to the patient, as well as increase health care costs and infection transmission possibility. Patients infected simultaneously with human immunodeficiency virus and Mycobacterium tuberculosis are a constant and worrying challenge for the scientific community which will research and develop new methods of diagnosis, new drugs and new therapies. Nowadays there are new tuberculosis diagnosis methods and some of which are already in clinical trial phases. These methods have high sensitivity, but do not replace the microbiological examination for isolation and culture of Mycobacterium spp. However, in clinical practice, microbiological, imaging, clinical and epidemiological data integration provide the best diagnosis and treatment possible. Consequently, throughout this paper, the different methods of diagnosis of human tuberculosis with its advantages and disadvantages will be covered, describing new omics and ultra-fast methods to increase knowledge and obtain a rapid diagnosis of tuberculosis.
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Affiliation(s)
- Patrícia Poeta
- a Department of Veterinary Sciences , University of Trás-os-Montes and Alto Douro (UTAD) , Vila Real , Portugal.,b Department of Genetics and Biotechnology, University of Trás-os-Montes and Alto Douro , Vila Real , Portugal
| | - Vanessa Silva
- a Department of Veterinary Sciences , University of Trás-os-Montes and Alto Douro (UTAD) , Vila Real , Portugal.,b Department of Genetics and Biotechnology, University of Trás-os-Montes and Alto Douro , Vila Real , Portugal.,c Functional Genomics and Proteomics Unit , University of Tras-os-Montes and Alto Douro (UTAD) , Vila Real , Portugal.,d Associated Laboratory for Green Chemistry (LAQV-REQUIMTE) , University NOVA of Lisboa , Lisboa , Caparica, Portugal
| | - Andreia Guedes
- a Department of Veterinary Sciences , University of Trás-os-Montes and Alto Douro (UTAD) , Vila Real , Portugal
| | - José Eduardo Pereira
- a Department of Veterinary Sciences , University of Trás-os-Montes and Alto Douro (UTAD) , Vila Real , Portugal.,e CECAV, Centro de Ciência Animal e Veterinária , Universidade de Trás-os-Montes e Alto Douro , Vila Real , Portugal
| | - Ana Cláudia Coelho
- a Department of Veterinary Sciences , University of Trás-os-Montes and Alto Douro (UTAD) , Vila Real , Portugal.,e CECAV, Centro de Ciência Animal e Veterinária , Universidade de Trás-os-Montes e Alto Douro , Vila Real , Portugal
| | - Gilberto Igrejas
- b Department of Genetics and Biotechnology, University of Trás-os-Montes and Alto Douro , Vila Real , Portugal.,c Functional Genomics and Proteomics Unit , University of Tras-os-Montes and Alto Douro (UTAD) , Vila Real , Portugal.,d Associated Laboratory for Green Chemistry (LAQV-REQUIMTE) , University NOVA of Lisboa , Lisboa , Caparica, Portugal
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Collins JM, Walker DI, Jones DP, Tukvadze N, Liu KH, Tran VT, Uppal K, Frediani JK, Easley KA, Shenvi N, Khadka M, Ortlund EA, Kempker RR, Blumberg HM, Ziegler TR. High-resolution plasma metabolomics analysis to detect Mycobacterium tuberculosis-associated metabolites that distinguish active pulmonary tuberculosis in humans. PLoS One 2018; 13:e0205398. [PMID: 30308073 PMCID: PMC6181350 DOI: 10.1371/journal.pone.0205398] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2018] [Accepted: 09/25/2018] [Indexed: 12/01/2022] Open
Abstract
Introduction Pulmonary tuberculosis (TB) is a major worldwide health problem that lacks robust blood-based biomarkers for detection of active disease. High-resolution metabolomics (HRM) is an innovative method to discover low-abundance metabolites as putative blood biomarkers to detect TB disease, including those known to be produced by the causative organism, Mycobacterium tuberculosis (Mtb). Methods We used HRM profiling to measure the plasma metabolome for 17 adults with active pulmonary TB disease and 16 of their household contacts without active TB. We used a suspect screening approach to identify metabolites previously described in cell culture studies of Mtb based on retention time and accurate mass matches. Results The association of relative metabolite abundance in active TB disease subjects compared to their household contacts predicted three Mtb-associated metabolites that were significantly increased in the active TB patients based on accurate mass matches: phosphatidylglycerol (PG) (16:0_18:1), lysophosphatidylinositol (Lyso-PI) (18:0) and acylphosphatidylinositol mannoside (Ac1PIM1) (56:1) (p<0.001 for all). These three metabolites provided excellent classification accuracy for active TB disease (AUC = 0.97). Ion dissociation spectra (tandem MS/MS) supported the identification of PG (16:0_18:1) and Lyso-PI (18:0) in the plasma of patients with active TB disease, though the identity of Ac1PIM1 could not be definitively confirmed. Conclusions Presence of the Mtb-associated lipid metabolites PG (16:0_18:1) and Lyso-PI (18:0) in plasma accurately identified patients with active TB disease. Consistency of in vitro and in vivo data suggests suitability for exploring these in future studies for possible development as TB disease biomarkers.
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Affiliation(s)
- Jeffrey M. Collins
- Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, United States of America
- * E-mail:
| | - Douglas I. Walker
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
| | - Dean P. Jones
- Clinical Biomarkers Laboratory, Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, United States of America
| | - Nestani Tukvadze
- National Center for Tuberculosis and Lung Disease, Tbilisi, Georgia
| | - Ken H. Liu
- Clinical Biomarkers Laboratory, Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, United States of America
| | - ViLinh T. Tran
- Clinical Biomarkers Laboratory, Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, United States of America
| | - Karan Uppal
- Clinical Biomarkers Laboratory, Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, United States of America
| | - Jennifer K. Frediani
- Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, Georgia, United States of America
| | - Kirk A. Easley
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
| | - Neeta Shenvi
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
| | - Manoj Khadka
- Emory Integrated Lipidomics Core, Department of Biochemistry, Emory University School of Medicine, Atlanta, Georgia, United States of America
| | - Eric A. Ortlund
- Emory Integrated Lipidomics Core, Department of Biochemistry, Emory University School of Medicine, Atlanta, Georgia, United States of America
| | - Russell R. Kempker
- Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, United States of America
| | - Henry M. Blumberg
- Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, United States of America
| | - Thomas R. Ziegler
- Division of Endocrinology, Metabolism and Lipids and Center for Clinical and Molecular Nutrition, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, United States of America
- Section of Endocrinology, Atlanta Veterans Affairs Medical Center, Atlanta, Georgia, United States of America
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Chong YK, Ho CC, Leung SY, Lau SK, Woo PC. Clinical Mass Spectrometry in the Bioinformatics Era: A Hitchhiker's Guide. Comput Struct Biotechnol J 2018; 16:316-334. [PMID: 30237866 PMCID: PMC6138949 DOI: 10.1016/j.csbj.2018.08.003] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Revised: 08/20/2018] [Accepted: 08/21/2018] [Indexed: 02/06/2023] Open
Abstract
Mass spectrometry (MS) is a sensitive, specific and versatile analytical technique in the clinical laboratory that has recently undergone rapid development. From initial use in metabolic profiling, it has matured into applications including clinical toxicology assays, target hormone and metabolite quantitation, and more recently, rapid microbial identification and antimicrobial resistance detection by matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). In this mini-review, we first succinctly outline the basics of clinical mass spectrometry. Examples of hard ionization (electron ionization) and soft ionization (electrospray ionization, MALDI) are presented to demonstrate their clinical applications. Next, a conceptual discourse on mass selection and determination is presented: quadrupole mass filter, time-of-flight mass spectrometer and the Orbitrap; and MS/MS (tandem-in-space, tandem-in-time and data acquisition), illustrated with clinical examples. Current applications in (1) bacterial and fungal identification, antimicrobial susceptibility testing and phylogenetic classification, (2) general unknown urine toxicology screening and expanded new-born metabolic screening and (3) clinical metabolic profiling by gas chromatography are outlined. Finally, major limitations of MS-based techniques, including the technical challenges of matrix effect and isobaric interference; and novel challenges in the post-genomic era, such as protein molecular variants, are critically discussed from the perspective of service laboratories. Computer technology and structural biology have played important roles in the maturation of this field. MS-based techniques have the potential to replace current analytical techniques, and existing expertise and instrument will undergo rapid evolution. Significant automation and adaptation to regulatory requirements are underway. Mass spectrometry is unleashing its potentials in clinical laboratories.
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Affiliation(s)
- Yeow-Kuan Chong
- Hospital Authority Toxicology Reference Laboratory, Department of Pathology, Princess Margaret Hospital (PMH), Kowloon, Hong Kong
- Chemical Pathology and Medical Genetics, Department of Pathology, Princess Margaret Hospital (PMH), Kowloon, Hong Kong
| | - Chi-Chun Ho
- Division of Chemical Pathology, Department of Clinical Pathology, Pamela Youde Nethersole Eastern Hospital (PYNEH), Hong Kong
- Division of Clinical Biochemistry, Department of Pathology, Queen Mary Hospital (QMH), Hong Kong
- Centre for Genomic Sciences, The University of Hong Kong, Hong Kong
- Department of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong
| | - Shui-Yee Leung
- Department of Ocean Science, School of Science, The Hong Kong University of Science and Technology, Kowloon, Hong Kong
| | - Susanna K.P. Lau
- Department of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, The University of Hong Kong, Hong Kong
- Research Centre of Infection and Immunology, The University of Hong Kong, Hong Kong
- Carol Yu Centre for Infection, The University of Hong Kong, Hong Kong
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The University of Hong Kong, Hong Kong
| | - Patrick C.Y. Woo
- Department of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, The University of Hong Kong, Hong Kong
- Research Centre of Infection and Immunology, The University of Hong Kong, Hong Kong
- Carol Yu Centre for Infection, The University of Hong Kong, Hong Kong
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The University of Hong Kong, Hong Kong
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Salgado-Bustamante M, Rocha-Viggiano AK, Rivas-Santiago C, Magaña-Aquino M, López JA, López-Hernández Y. Metabolomics applied to the discovery of tuberculosis and diabetes mellitus biomarkers. Biomark Med 2018; 12:1001-1013. [PMID: 30043640 DOI: 10.2217/bmm-2018-0050] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Tuberculosis (TB) and diabetes mellitus Type 2 (DM2) are two diseases as ancient as they are harmful to human health. The outcome for both diseases in part depends on immune and metabolic individual responses. DM2 is increasing yearly, mainly due to environmental, genetic and lifestyle habits. There are multiple evidence that DM2 is one of the most important risk factor of becoming infected with TB or reactivating latent TB. Mass spectrometry-based metabolomics is an important tool for elucidating the metabolites and metabolic pathways that influence the immune responses to M. tuberculosis infection during diabetes. We provide an up-to-date review highlighting the importance and benefit of metabolomics for identifying biomarkers as candidate molecules for diagnosis, disease activity or prognosis.
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Affiliation(s)
- Mariana Salgado-Bustamante
- Biochemistry Department, Medicine Faculty, Universidad Autonoma de San Luis Potosi, San Luis Potosi, Mexico
| | - Ana K Rocha-Viggiano
- Biochemistry Department, Medicine Faculty, Universidad Autonoma de San Luis Potosi, San Luis Potosi, Mexico
| | - César Rivas-Santiago
- CONACyT, Unidad Academica de Ciencias Biologicas, Universidad Autonoma de Zacatecas, Zacatecas, Mexico
| | - Martín Magaña-Aquino
- Infectology Department, Hospital Central Ignacio Morones Prieto, San Luis Potosi, Mexico
| | - Jesús A López
- MicroRNAs Laboratory, Unidad Academica de Ciencias Biologicas, Universidad Autonoma de Zacatecas, Zacatecas, Mexico
| | - Yamilé López-Hernández
- CONACyT, Unidad Academica de Ciencias Biologicas, Universidad Autonoma de Zacatecas, Zacatecas, Mexico
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Tuberculosis: advances and challenges in development of new diagnostics and biomarkers. THE LANCET. INFECTIOUS DISEASES 2018; 18:e199-e210. [PMID: 29580818 DOI: 10.1016/s1473-3099(18)30111-7] [Citation(s) in RCA: 204] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2017] [Revised: 12/18/2017] [Accepted: 01/02/2018] [Indexed: 11/23/2022]
Abstract
Tuberculosis remains the leading cause of death from an infectious disease worldwide. Early and accurate diagnosis and detection of drug-sensitive and drug-resistant tuberculosis is essential for achieving global tuberculosis control. Despite the introduction of the Xpert MTB/RIF assay as the first-line rapid tuberculosis diagnostic test, the gap between global estimates of incidence and new case notifications is 4·1 million people. More accurate, rapid, and cost-effective screening tests are needed to improve case detection. Diagnosis of extrapulmonary tuberculosis and tuberculosis in children, people living with HIV, and pregnant women remains particularly problematic. The diagnostic molecular technology landscape has continued to expand, including the development of tests for resistance to several antituberculosis drugs. Biomarkers are urgently needed to indicate progression from latent infection to clinical disease, to predict risk of reactivation after cure, and to provide accurate endpoints for drug and vaccine trials. Sophisticated bioinformatic computational tools and systems biology approaches are being applied to the discovery and validation of biomarkers, with substantial progress taking place. New data have been generated from the study of T-cell responses and T-cell function, serological studies, flow cytometric-based assays, and protein and gene expression studies. Alternative diagnostic strategies under investigation as potential screening and triaging tools include non-sputum-based detection with breath-based tests and automated digital radiography. We review developments and key achievements in the search for new tuberculosis diagnostics and biomarkers. We highlight gaps and challenges in evaluation and rollout of new diagnostics and biomarkers, and prioritise areas needing further investment, including impact assessment and cost-benefit studies.
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Uji M, Yokoyama Y, Ohbuchi K, Tsuchiya K, Sadakane C, Shimobori C, Yamamoto M, Nagino M. Exploration of serum biomarkers for predicting the response to Inchinkoto (ICKT), a Japanese traditional herbal medicine. Metabolomics 2017; 13:155. [PMID: 31375927 PMCID: PMC6153689 DOI: 10.1007/s11306-017-1292-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/29/2017] [Accepted: 10/31/2017] [Indexed: 12/24/2022]
Abstract
INTRODUCTION In patients with obstructive jaundice, biliary drainage sometimes fails to result in improvement. A pharmaceutical-grade choleretic herbal medicine, Inchinkoto (ICKT), has been proposed to exert auxiliary effects on biliary drainage; however, its effects are variable among patients. OBJECTIVES The aim of this study is to explore serum biomarkers that are associated with pharmaceutical efficacy of ICKT. METHODS Obstructive jaundice patients who underwent external biliary decompression were enrolled (n = 37). ICKT was given orally 3 times a day at daily dose of 7.5 g. Serum and bile samples were collected before, 3 h after, and 24 h after ICKT administration. The concentrations of total bilirubin, direct bilirubin, and total bile acid in bile specimens were measured. Metabolites in serum samples were comprehensively profiled using LC-MS/MS and GC-MS/MS. Pharmacokinetic analysis of major ICKT components was also performed. RESULTS ICKT administration significantly decreased serum ALT and increased bile volume after 24 h. The serum concentrations of ICKT components were not well correlated with the efficacy of ICKT. However, the ratio of 2-hydroxyisobutyric acid to arachidonic acid and the ratio of glutaric acid to niacinamide, exhibited good performance as biomarkers for the efficacy of ICKT on bile flow and ALT, respectively. Additionally, comprehensive correlation analysis revealed that serum glucuronic acid was highly correlated with serum total bilirubin, suggesting that this metabolite may be deeply involved in the pathogenesis of jaundice. CONCLUSIONS The present study indicates that ICKT is efficacious and provides candidates for predicting ICKT efficacy. Further validation studies are warranted.
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Affiliation(s)
- Masahito Uji
- Division of Surgical Oncology, Department of Surgery, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Japan
| | - Yukihiro Yokoyama
- Division of Surgical Oncology, Department of Surgery, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Japan.
| | | | | | | | | | | | - Masato Nagino
- Division of Surgical Oncology, Department of Surgery, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, Japan
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Sun L, Li JQ, Ren N, Qi H, Dong F, Xiao J, Xu F, Jiao WW, Shen C, Song WQ, Shen AD. Utility of Novel Plasma Metabolic Markers in the Diagnosis of Pediatric Tuberculosis: A Classification and Regression Tree Analysis Approach. J Proteome Res 2016; 15:3118-25. [PMID: 27451809 DOI: 10.1021/acs.jproteome.6b00228] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Although tuberculosis (TB) has been the greatest killer due to a single infectious disease, pediatric TB is still hard to diagnose because of the lack of sensitive biomarkers. Metabolomics is increasingly being applied in infectious diseases. But little is known regarding metabolic biomarkers in children with TB. A combination of a NMR-based plasma metabolic method and classification and regression tree (CART) analysis was used to provide a broader range of applications in TB diagnosis in our study. Plasma samples obtained from 28 active TB children and 37 non-TB controls (including 21 RTIs and 16 healthy children) were analyzed by an orthogonal partial least-squares discriminant analysis (OPLS-DA) model, and 17 metabolites were identified that can separate children with TB from non-TB controls. CART analysis was then used to choose 3 of the markers, l-valine, pyruvic acid, and betaine, with the least error. The sensitivity, specificity, and area under the curve (AUC) of the 3 metabolites is 85.7% (24/28, 95% CI, 66.4%, 95.3%), 94.6% (35/37, 95% CI, 80.5%, 99.1%), and 0.984(95% CI, 0.917, 1.000), respectively. The 3 metabolites demonstrated sensitivity of 82.4% (14/17, 95% CI, 55.8%, 95.3%) and specificity of 83.9% (26/31, 95% CI, 65.5%, 93.9%), respectively, in 48 blinded subjects in an independent cohort. Taken together, the novel plasma metabolites are potentially useful for diagnosis of pediatric TB and would provide insights into the disease mechanism.
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Affiliation(s)
- Lin Sun
- Key Laboratory of Major Diseases in Children, Ministry of Education, National Key Discipline of Pediatrics (Capital Medical University), Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University , 100045 Beijing, People's Republic of China
| | - Jie-Qiong Li
- Key Laboratory of Major Diseases in Children, Ministry of Education, National Key Discipline of Pediatrics (Capital Medical University), Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University , 100045 Beijing, People's Republic of China
| | - Na Ren
- Key Laboratory of Major Diseases in Children, Ministry of Education, National Key Discipline of Pediatrics (Capital Medical University), Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University , 100045 Beijing, People's Republic of China
| | - Hui Qi
- Key Laboratory of Major Diseases in Children, Ministry of Education, National Key Discipline of Pediatrics (Capital Medical University), Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University , 100045 Beijing, People's Republic of China
| | - Fang Dong
- Key Laboratory of Major Diseases in Children, Ministry of Education, National Key Discipline of Pediatrics (Capital Medical University), Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University , 100045 Beijing, People's Republic of China
| | - Jing Xiao
- Key Laboratory of Major Diseases in Children, Ministry of Education, National Key Discipline of Pediatrics (Capital Medical University), Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University , 100045 Beijing, People's Republic of China
| | - Fang Xu
- Key Laboratory of Major Diseases in Children, Ministry of Education, National Key Discipline of Pediatrics (Capital Medical University), Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University , 100045 Beijing, People's Republic of China
| | - Wei-Wei Jiao
- Key Laboratory of Major Diseases in Children, Ministry of Education, National Key Discipline of Pediatrics (Capital Medical University), Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University , 100045 Beijing, People's Republic of China
| | - Chen Shen
- Key Laboratory of Major Diseases in Children, Ministry of Education, National Key Discipline of Pediatrics (Capital Medical University), Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University , 100045 Beijing, People's Republic of China
| | - Wen-Qi Song
- Key Laboratory of Major Diseases in Children, Ministry of Education, National Key Discipline of Pediatrics (Capital Medical University), Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University , 100045 Beijing, People's Republic of China
| | - A-Dong Shen
- Key Laboratory of Major Diseases in Children, Ministry of Education, National Key Discipline of Pediatrics (Capital Medical University), Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University , 100045 Beijing, People's Republic of China
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Haas CT, Roe JK, Pollara G, Mehta M, Noursadeghi M. Diagnostic 'omics' for active tuberculosis. BMC Med 2016; 14:37. [PMID: 27005907 PMCID: PMC4804573 DOI: 10.1186/s12916-016-0583-9] [Citation(s) in RCA: 56] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2015] [Accepted: 02/08/2016] [Indexed: 12/12/2022] Open
Abstract
The decision to treat active tuberculosis (TB) is dependent on microbiological tests for the organism or evidence of disease compatible with TB in people with a high demographic risk of exposure. The tuberculin skin test and peripheral blood interferon-γ release assays do not distinguish active TB from a cleared or latent infection. Microbiological culture of mycobacteria is slow. Moreover, the sensitivities of culture and microscopy for acid-fast bacilli and nucleic acid detection by PCR are often compromised by difficulty in obtaining samples from the site of disease. Consequently, we need sensitive and rapid tests for easily obtained clinical samples, which can be deployed to assess patients exposed to TB, discriminate TB from other infectious, inflammatory or autoimmune diseases, and to identify subclinical TB in HIV-1 infected patients prior to commencing antiretroviral therapy. We discuss the evaluation of peripheral blood transcriptomics, proteomics and metabolomics to develop the next generation of rapid diagnostics for active TB. We catalogue the studies published to date seeking to discriminate active TB from healthy volunteers, patients with latent infection and those with other diseases. We identify the limitations of these studies and the barriers to their adoption in clinical practice. In so doing, we aim to develop a framework to guide our approach to discovery and development of diagnostic biomarkers for active TB.
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Affiliation(s)
- Carolin T Haas
- Division of Infection and Immunity, University College London, Cruciform Building, Gower Street, London, WC1E 6BT, UK
| | - Jennifer K Roe
- Division of Infection and Immunity, University College London, Cruciform Building, Gower Street, London, WC1E 6BT, UK
| | - Gabriele Pollara
- Division of Infection and Immunity, University College London, Cruciform Building, Gower Street, London, WC1E 6BT, UK
| | - Meera Mehta
- Division of Infection and Immunity, University College London, Cruciform Building, Gower Street, London, WC1E 6BT, UK
| | - Mahdad Noursadeghi
- Division of Infection and Immunity, University College London, Cruciform Building, Gower Street, London, WC1E 6BT, UK.
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Lau SKP, Lee KC, Lo GCS, Ding VSY, Chow WN, Ke TYH, Curreem SOT, To KKW, Ho DTY, Sridhar S, Wong SCY, Chan JFW, Hung IFN, Sze KH, Lam CW, Yuen KY, Woo PCY. Metabolomic Profiling of Plasma from Melioidosis Patients Using UHPLC-QTOF MS Reveals Novel Biomarkers for Diagnosis. Int J Mol Sci 2016; 17:307. [PMID: 26927094 PMCID: PMC4813170 DOI: 10.3390/ijms17030307] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2016] [Revised: 02/15/2016] [Accepted: 02/22/2016] [Indexed: 12/22/2022] Open
Abstract
To identify potential biomarkers for improving diagnosis of melioidosis, we compared plasma metabolome profiles of melioidosis patients compared to patients with other bacteremia and controls without active infection, using ultra-high-performance liquid chromatography-electrospray ionization-quadruple time-of-flight mass spectrometry. Principal component analysis (PCA) showed that the metabolomic profiles of melioidosis patients are distinguishable from bacteremia patients and controls. Using multivariate and univariate analysis, 12 significant metabolites from four lipid classes, acylcarnitine (n = 6), lysophosphatidylethanolamine (LysoPE) (n = 3), sphingomyelins (SM) (n = 2) and phosphatidylcholine (PC) (n = 1), with significantly higher levels in melioidosis patients than bacteremia patients and controls, were identified. Ten of the 12 metabolites showed area-under-receiver operating characteristic curve (AUC) >0.80 when compared both between melioidosis and bacteremia patients, and between melioidosis patients and controls. SM(d18:2/16:0) possessed the largest AUC when compared, both between melioidosis and bacteremia patients (AUC 0.998, sensitivity 100% and specificity 91.7%), and between melioidosis patients and controls (AUC 1.000, sensitivity 96.7% and specificity 100%). Our results indicate that metabolome profiling might serve as a promising approach for diagnosis of melioidosis using patient plasma, with SM(d18:2/16:0) representing a potential biomarker. Since the 12 metabolites were related to various pathways for energy and lipid metabolism, further studies may reveal their possible role in the pathogenesis and host response in melioidosis.
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Affiliation(s)
- Susanna K P Lau
- State Key Laboratory of Emerging Infectious Diseases, The University of Hong Kong, Pokfulam, Hong Kong, China.
- Research Centre of Infection and Immunology, The University of Hong Kong, Pokfulam, Hong Kong, China.
- Carol Yu Centre for Infection, The University of Hong Kong, Pokfulam, Hong Kong, China.
- Department of Microbiology, The University of Hong Kong, Pokfulam, Hong Kong, China.
| | - Kim-Chung Lee
- Department of Microbiology, The University of Hong Kong, Pokfulam, Hong Kong, China.
| | - George C S Lo
- Department of Microbiology, The University of Hong Kong, Pokfulam, Hong Kong, China.
| | - Vanessa S Y Ding
- Department of Microbiology, The University of Hong Kong, Pokfulam, Hong Kong, China.
| | - Wang-Ngai Chow
- Department of Microbiology, The University of Hong Kong, Pokfulam, Hong Kong, China.
| | - Tony Y H Ke
- Department of Microbiology, The University of Hong Kong, Pokfulam, Hong Kong, China.
| | - Shirly O T Curreem
- Department of Microbiology, The University of Hong Kong, Pokfulam, Hong Kong, China.
| | - Kelvin K W To
- State Key Laboratory of Emerging Infectious Diseases, The University of Hong Kong, Pokfulam, Hong Kong, China.
- Research Centre of Infection and Immunology, The University of Hong Kong, Pokfulam, Hong Kong, China.
- Carol Yu Centre for Infection, The University of Hong Kong, Pokfulam, Hong Kong, China.
- Department of Microbiology, The University of Hong Kong, Pokfulam, Hong Kong, China.
| | - Deborah T Y Ho
- Department of Microbiology, The University of Hong Kong, Pokfulam, Hong Kong, China.
| | - Siddharth Sridhar
- Department of Microbiology, The University of Hong Kong, Pokfulam, Hong Kong, China.
| | - Sally C Y Wong
- Department of Microbiology, The University of Hong Kong, Pokfulam, Hong Kong, China.
| | - Jasper F W Chan
- Department of Microbiology, The University of Hong Kong, Pokfulam, Hong Kong, China.
| | - Ivan F N Hung
- Research Centre of Infection and Immunology, The University of Hong Kong, Pokfulam, Hong Kong, China.
- Department of Medicine, The University of Hong Kong, Pokfulam, Hong Kong, China.
| | - Kong-Hung Sze
- Department of Microbiology, The University of Hong Kong, Pokfulam, Hong Kong, China.
| | - Ching-Wan Lam
- Department of Pathology, The University of Hong Kong, Pokfulam, Hong Kong, China.
| | - Kwok-Yung Yuen
- State Key Laboratory of Emerging Infectious Diseases, The University of Hong Kong, Pokfulam, Hong Kong, China.
- Research Centre of Infection and Immunology, The University of Hong Kong, Pokfulam, Hong Kong, China.
- Carol Yu Centre for Infection, The University of Hong Kong, Pokfulam, Hong Kong, China.
- Department of Microbiology, The University of Hong Kong, Pokfulam, Hong Kong, China.
| | - Patrick C Y Woo
- State Key Laboratory of Emerging Infectious Diseases, The University of Hong Kong, Pokfulam, Hong Kong, China.
- Research Centre of Infection and Immunology, The University of Hong Kong, Pokfulam, Hong Kong, China.
- Carol Yu Centre for Infection, The University of Hong Kong, Pokfulam, Hong Kong, China.
- Department of Microbiology, The University of Hong Kong, Pokfulam, Hong Kong, China.
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