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Wu M, Yang Q, Yang C, Han J, Liu H, Qiao L, Duan H, Xing L, Liu Q, Dong L, Wang Q, Zuo L. Characteristics of plasma exosomes in drug-resistant tuberculosis patients. Tuberculosis (Edinb) 2023; 141:102359. [PMID: 37329682 DOI: 10.1016/j.tube.2023.102359] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 05/25/2023] [Accepted: 05/29/2023] [Indexed: 06/19/2023]
Abstract
BACKGROUND Increasing prevalence of drug-resistant tuberculosis (DR-TB) poses a major challenge to the early detection and effective control of tuberculosis (TB). Exosomes carrying proteins and nucleic acid mediate intercellular communication between host and pathogen including Mycobacterium tuberculosis. However, molecular events of exosomes indicating the status and development of DR-TB remain unknown. This study determined the proteomics of exosome in DR-TB and explored the potential pathogenesis of DR-TB. METHODS Plasma samples were collected from 17 DR-TB patients and 33 non-drug-resistant tuberculosis (NDR-TB) patients using grouped case-control study design. After exosomes of plasma were isolated and confirmed by compositional and morphological measurement for exosomal characteristics, a label-free quantitative proteomics of exosomes was performed and differential protein components were determined via bioinformatics analysis. RESULTS Compared with the NDR-TB group, we identified 16 up-regulated proteins and 10 down-regulated proteins in the DR-TB group. The down-regulated proteins were mainly apolipoproteins and mainly enriched in cholesterol metabolism-related pathways. Apolipoproteins family including APOA1, APOB, APOC1 were key proteins in protein-protein interaction network. CONCLUSION Differentially expressed proteins in the exosomes may indicate the status of DR-TB from NDR-TB. Apolipoproteins family including APOA1, APOB, APOC1 may be involved in the pathogenesis of DR-TB by regulating cholesterol metabolism via exosomes.
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Affiliation(s)
- Mingrui Wu
- Key Laboratory of Cellular Physiology, Ministry of Education, The Department of Physiology, School of Basic Sciences, Shanxi Medical University, Taiyuan, 030001, China
| | - Qianwei Yang
- Shanxi Provincial Key Laboratory for Medical Molecular Cell Biology, Key Laboratory of Chemical Biology and Molecular Engineering of Ministry of Education, Institutes of Biomedical Sciences, Shanxi University, Taiyuan, 030006, China
| | - Caiting Yang
- Shanxi Provincial Key Laboratory for Medical Molecular Cell Biology, Key Laboratory of Chemical Biology and Molecular Engineering of Ministry of Education, Institutes of Biomedical Sciences, Shanxi University, Taiyuan, 030006, China
| | - Jie Han
- Shanxi Provincial Key Laboratory for Medical Molecular Cell Biology, Key Laboratory of Chemical Biology and Molecular Engineering of Ministry of Education, Institutes of Biomedical Sciences, Shanxi University, Taiyuan, 030006, China
| | - Hai Liu
- Shanxi Provincial Key Laboratory for Medical Molecular Cell Biology, Key Laboratory of Chemical Biology and Molecular Engineering of Ministry of Education, Institutes of Biomedical Sciences, Shanxi University, Taiyuan, 030006, China
| | - Lingran Qiao
- Key Laboratory of Cellular Physiology, Ministry of Education, The Department of Physiology, School of Basic Sciences, Shanxi Medical University, Taiyuan, 030001, China
| | - Huiping Duan
- The Fourth People's Hospital of Taiyuan, Taiyuan, 030024, China
| | - Li Xing
- Shanxi Provincial Key Laboratory for Medical Molecular Cell Biology, Key Laboratory of Chemical Biology and Molecular Engineering of Ministry of Education, Institutes of Biomedical Sciences, Shanxi University, Taiyuan, 030006, China
| | - Qunqun Liu
- The Fourth People's Hospital of Taiyuan, Taiyuan, 030024, China
| | - Li Dong
- Shanxi Provincial Key Laboratory for Medical Molecular Cell Biology, Key Laboratory of Chemical Biology and Molecular Engineering of Ministry of Education, Institutes of Biomedical Sciences, Shanxi University, Taiyuan, 030006, China.
| | - Quanhong Wang
- The Fourth People's Hospital of Taiyuan, Taiyuan, 030024, China.
| | - Lin Zuo
- Key Laboratory of Cellular Physiology, Ministry of Education, The Department of Physiology, School of Basic Sciences, Shanxi Medical University, Taiyuan, 030001, China.
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Mousavian Z, Folkesson E, Fröberg G, Foroogh F, Correia-Neves M, Bruchfeld J, Källenius G, Sundling C. A protein signature associated with active tuberculosis identified by plasma profiling and network-based analysis. iScience 2022; 25:105652. [PMID: 36561889 PMCID: PMC9763869 DOI: 10.1016/j.isci.2022.105652] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 09/19/2022] [Accepted: 11/18/2022] [Indexed: 11/23/2022] Open
Abstract
Annually, approximately 10 million people are diagnosed with active tuberculosis (TB), and 1.4 million die of the disease. If left untreated, each person with active TB will infect 10-15 new individuals. The lack of non-sputum-based diagnostic tests leads to delayed diagnoses of active pulmonary TB cases, contributing to continued disease transmission. In this exploratory study, we aimed to identify biomarkers associated with active TB. We assessed the plasma levels of 92 proteins associated with inflammation in individuals with active TB (n = 20), latent TB (n = 14), or healthy controls (n = 10). Using co-expression network analysis, we identified one module of proteins with strong association with active TB. We removed proteins from the module that had low abundance or were associated with non-TB diseases in published transcriptomic datasets, resulting in a 12-protein plasma signature that was highly enriched in individuals with pulmonary and extrapulmonary TB and was further associated with disease severity.
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Affiliation(s)
- Zaynab Mousavian
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- School of Mathematics, Statistics and Computer Science, College of Science, University of Tehran, Tehran, Iran
| | - Elin Folkesson
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Gabrielle Fröberg
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Microbiology, Karolinska University Laboratory, Karolinska University Hospital, Stockholm, Sweden
| | - Fariba Foroogh
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Margarida Correia-Neves
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Life and Health Sciences Research Institute, School of Medicine, University of Minho, Braga, Portugal
- ICVS/3B’s, PT Government Associate Laboratory, Braga, Portugal
| | - Judith Bruchfeld
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Gunilla Källenius
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Christopher Sundling
- Division of Infectious Diseases, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden
- Corresponding author
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3
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Mass Spectrometry-Based Proteomic and Metabolomic Profiling of Serum Samples for Discovery and Validation of Tuberculosis Diagnostic Biomarker Signature. Int J Mol Sci 2022; 23:ijms232213733. [PMID: 36430211 PMCID: PMC9694769 DOI: 10.3390/ijms232213733] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 10/26/2022] [Accepted: 11/03/2022] [Indexed: 11/11/2022] Open
Abstract
Tuberculosis (TB) is a transmissible disease listed as one of the 10 leading causes of death worldwide (10 million infected in 2019). A swift and precise diagnosis is essential to forestall its transmission, for which the discovery of effective diagnostic biomarkers is crucial. In this study, we aimed to discover molecular biomarkers for the early diagnosis of tuberculosis. Two independent cohorts comprising 29 and 34 subjects were assayed by proteomics, and 49 were included for metabolomic analysis. All subjects were arranged into three experimental groups—healthy controls (controls), latent TB infection (LTBI), and TB patients. LC-MS/MS blood serum protein and metabolite levels were submitted to univariate, multivariate, and ROC analysis. From the 149 proteins quantified in the discovery set, 25 were found to be differentially abundant between controls and TB patients. The AUC, specificity, and sensitivity, determined by ROC statistical analysis of the model composed of four of these proteins considering both proteomic sets, were 0.96, 93%, and 91%, respectively. The five metabolites (9-methyluric acid, indole-3-lactic acid, trans-3-indoleacrylic acid, hexanoylglycine, and N-acetyl-L-leucine) that better discriminate the control and TB patient groups (VIP > 1.75) from a total of 92 metabolites quantified in both ionization modes were submitted to ROC analysis. An AUC = 1 was determined, with all samples being correctly assigned to the respective experimental group. An integrated ROC analysis enrolling one protein and four metabolites was also performed for the common control and TB patients in the proteomic and metabolomic groups. This combined signature correctly assigned the 12 controls and 12 patients used only for prediction (AUC = 1, specificity = 100%, and sensitivity = 100%). This multiomics approach revealed a biomarker signature for tuberculosis diagnosis that could be potentially used for developing a point-of-care diagnosis clinical test.
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Heyckendorf J, Georghiou SB, Frahm N, Heinrich N, Kontsevaya I, Reimann M, Holtzman D, Imperial M, Cirillo DM, Gillespie SH, Ruhwald M. Tuberculosis Treatment Monitoring and Outcome Measures: New Interest and New Strategies. Clin Microbiol Rev 2022; 35:e0022721. [PMID: 35311552 PMCID: PMC9491169 DOI: 10.1128/cmr.00227-21] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Despite the advent of new diagnostics, drugs and regimens, tuberculosis (TB) remains a global public health threat. A significant challenge for TB control efforts has been the monitoring of TB therapy and determination of TB treatment success. Current recommendations for TB treatment monitoring rely on sputum and culture conversion, which have low sensitivity and long turnaround times, present biohazard risk, and are prone to contamination, undermining their usefulness as clinical treatment monitoring tools and for drug development. We review the pipeline of molecular technologies and assays that serve as suitable substitutes for current culture-based readouts for treatment response and outcome with the potential to change TB therapy monitoring and accelerate drug development.
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Affiliation(s)
- Jan Heyckendorf
- Department of Medicine I, University Hospital Schleswig-Holstein, Kiel, Germany
- Division of Clinical Infectious Diseases, Research Center Borstel, Borstel, Germany
- German Center for Infection Research (DZIF), Braunschweig, Germany
- International Health/Infectious Diseases, University of Lübeck, Lübeck, Germany
| | | | - Nicole Frahm
- Bill & Melinda Gates Medical Research Institute, Cambridge, Massachusetts, USA
| | - Norbert Heinrich
- Division of Infectious Diseases and Tropical Medicine, Medical Centre of the University of Munich (LMU), Munich, Germany
| | - Irina Kontsevaya
- Division of Clinical Infectious Diseases, Research Center Borstel, Borstel, Germany
- German Center for Infection Research (DZIF), Braunschweig, Germany
- International Health/Infectious Diseases, University of Lübeck, Lübeck, Germany
| | - Maja Reimann
- Division of Clinical Infectious Diseases, Research Center Borstel, Borstel, Germany
- German Center for Infection Research (DZIF), Braunschweig, Germany
- International Health/Infectious Diseases, University of Lübeck, Lübeck, Germany
| | - David Holtzman
- FIND, the Global Alliance for Diagnostics, Geneva, Switzerland
| | - Marjorie Imperial
- University of California San Francisco, San Francisco, California, USA, United States
| | - Daniela M. Cirillo
- Emerging Bacterial Pathogens Unit, Division of Immunology, Transplantation and Infectious Diseases, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Stephen H. Gillespie
- School of Medicine, University of St Andrewsgrid.11914.3c, St Andrews, Fife, Scotland
| | - Morten Ruhwald
- FIND, the Global Alliance for Diagnostics, Geneva, Switzerland
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Garlant HN, Ellappan K, Hewitt M, Perumal P, Pekeleke S, Wand N, Southern J, Kumar SV, Belgode H, Abubakar I, Sinha S, Vasan S, Joseph NM, Kempsell KE. Evaluation of Host Protein Biomarkers by ELISA From Whole Lysed Peripheral Blood for Development of Diagnostic Tests for Active Tuberculosis. Front Immunol 2022; 13:854327. [PMID: 35720382 PMCID: PMC9205408 DOI: 10.3389/fimmu.2022.854327] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 02/28/2022] [Indexed: 11/23/2022] Open
Abstract
Tuberculosis (TB) remains a significant global health crisis and the number one cause of death for an infectious disease. The health consequences in high-burden countries are significant. Barriers to TB control and eradication are in part caused by difficulties in diagnosis. Improvements in diagnosis are required for organisations like the World Health Organisation (WHO) to meet their ambitious target of reducing the incidence of TB by 50% by the year 2025, which has become hard to reach due to the COVID-19 pandemic. Development of new tests for TB are key priorities of the WHO, as defined in their 2014 report for target product profiles (TPPs). Rapid triage and biomarker-based confirmatory tests would greatly enhance the diagnostic capability for identifying and diagnosing TB-infected individuals. Protein-based test methods e.g. lateral flow devices (LFDs) have a significant advantage over other technologies with regard to assay turnaround time (minutes as opposed to hours) field-ability, ease of use by relatively untrained staff and without the need for supporting laboratory infrastructure. Here we evaluate the diagnostic performance of nine biomarkers from our previously published biomarker qPCR validation study; CALCOCO2, CD274, CD52, GBP1, IFIT3, IFITM3, SAMD9L, SNX10 and TMEM49, as protein targets assayed by ELISA. This preliminary evaluation study was conducted to quantify the level of biomarker protein expression across latent, extra-pulmonary or pulmonary TB groups and negative controls, collected across the UK and India, in whole lysed blood samples (WLB). We also investigated associative correlations between the biomarkers and assessed their suitability for ongoing diagnostic test development, using receiver operating characteristic/area under the curve (ROC) analyses, singly and in panel combinations. The top performing single biomarkers for pulmonary TB versus controls were CALCOCO2, SAMD9L, GBP1, IFITM3, IFIT3 and SNX10. TMEM49 was also significantly differentially expressed but downregulated in TB groups. CD52 expression was not highly differentially expressed across most of the groups but may provide additional patient stratification information and some limited use for incipient latent TB infection. These show therefore great potential for diagnostic test development either in minimal configuration panels for rapid triage or more complex formulations to capture the diversity of disease presentations.
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Affiliation(s)
- Harriet N. Garlant
- Science Group: Research and Evaluation, UK Health Security Agency, Salisbury, United Kingdom
| | - Kalaiarasan Ellappan
- Department of Microbiology, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India
| | - Matthew Hewitt
- Science Group: Research and Evaluation, UK Health Security Agency, Salisbury, United Kingdom
| | - Prem Perumal
- Science Group: Research and Evaluation, UK Health Security Agency, Salisbury, United Kingdom
| | - Simon Pekeleke
- Science Group: Research and Evaluation, UK Health Security Agency, Salisbury, United Kingdom
| | - Nadina Wand
- Science Group: Research and Evaluation, UK Health Security Agency, Salisbury, United Kingdom
| | - Jo Southern
- School of Life & Medical Sciences, Mortimer Market Centre, University College London, London, United Kingdom
| | - Saka Vinod Kumar
- Department of Microbiology, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India
| | - Harish Belgode
- Department of Microbiology, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India
| | - Ibrahim Abubakar
- School of Life & Medical Sciences, Mortimer Market Centre, University College London, London, United Kingdom
| | - Sanjeev Sinha
- Department of Medicine, All India Institute for Medical Sciences, New Delhi, India
| | - Seshadri Vasan
- Department of Health Sciences, University of York, York, United Kingdom
| | - Noyal Mariya Joseph
- Department of Microbiology, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India
| | - Karen E. Kempsell
- Science Group: Research and Evaluation, UK Health Security Agency, Salisbury, United Kingdom
- *Correspondence: Karen E. Kempsell,
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Pitaloka DAE, Syamsunarno MRAAA, Abdulah R, Chaidir L. Omics Biomarkers for Monitoring Tuberculosis Treatment: A Mini-Review of Recent Insights and Future Approaches. Infect Drug Resist 2022; 15:2703-2711. [PMID: 35664683 PMCID: PMC9160605 DOI: 10.2147/idr.s366580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 05/20/2022] [Indexed: 11/23/2022] Open
Abstract
Poor sensitivity of sputum conversion for monitoring tuberculosis (TB) treatment that makes identification of a non-sputum-based biomarker is urgently needed. Monitoring biomarkers in TB treatment is used to decide whether critical thresholds have been reached and helps clinicians to conclude the therapeutic success. In this mini review, we highlight recent studies on omics-related contributes to identifying of a novel biomarker as surrogate markers for the cure and predicting future reactivation risk following TB treatment. We catalogue the studies published to seek the progress made in transcriptomics, proteomics, and metabolomics in pulmonary TB. We also discuss how integrative multi-omics data will provide further understanding and effective TB treatment, such as revealing the interrelationships at multiple molecular levels, facilitating the identification of biologically interconnected processes, and accelerating precision medicine in TB treatment. However, proper validation in prospective longitudinal studies with long-term follow-up and outcome assessment must be conducted before the biomarkers are utilized in clinical practice.
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Affiliation(s)
- Dian Ayu Eka Pitaloka
- Department of Pharmacology and Clinical Pharmacy, Faculty of Pharmacy, Universitas Padjadjaran, Sumedang, West Java, 45363, Indonesia
- Center for Translational Biomarker Research, Universitas Padjadjaran, Bandung, West Java, 40132, Indonesia
| | - Mas Rizky Anggun A A Syamsunarno
- Center for Translational Biomarker Research, Universitas Padjadjaran, Bandung, West Java, 40132, Indonesia
- Department of Biomedical Sciences, Faculty of Medicine, Universitas Padjadjaran, Sumedang, West Java, 45363, Indonesia
| | - Rizky Abdulah
- Department of Pharmacology and Clinical Pharmacy, Faculty of Pharmacy, Universitas Padjadjaran, Sumedang, West Java, 45363, Indonesia
- Center of Excellence in Higher Education for Pharmaceutical Care Innovation, Universitas Padjadjaran, Sumedang, West Java, 45363, Indonesia
| | - Lidya Chaidir
- Center for Translational Biomarker Research, Universitas Padjadjaran, Bandung, West Java, 40132, Indonesia
- Department of Biomedical Sciences, Faculty of Medicine, Universitas Padjadjaran, Sumedang, West Java, 45363, Indonesia
- Correspondence: Lidya Chaidir, Department of Biomedical Sciences, Faculty of Medicine, Universitas Padjadjaran, Sumedang, West Java, 45363, Indonesia, Tel +62-22-84288812, Email
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Mycobacterium tuberculosis Affects Protein and Lipid Content of Circulating Exosomes in Infected Patients Depending on Tuberculosis Disease State. Biomedicines 2022; 10:biomedicines10040783. [PMID: 35453532 PMCID: PMC9025801 DOI: 10.3390/biomedicines10040783] [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: 02/14/2022] [Revised: 03/15/2022] [Accepted: 03/23/2022] [Indexed: 11/25/2022] Open
Abstract
Tuberculosis (TB), which is caused by the bacterium Mycobacterium tuberculosis (Mtb), is still one of the deadliest infectious diseases. Understanding how the host and pathogen interact in active TB will have a significant impact on global TB control efforts. Exosomes are increasingly recognized as a means of cell-to-cell contact and exchange of soluble mediators. In the case of TB, exosomes are released from the bacillus and infected cells. In the present study, a comprehensive lipidomics and proteomics analysis of size exclusion chromatography-isolated plasma-derived exosomes from patients with TB lymphadenitis (TBL) and treated as well as untreated pulmonary TB (PTB) was performed to elucidate the possibility to utilize exosomes in diagnostics and knowledge building. According to our findings, exosome-derived lipids and proteins originate from both the host and Mtb in the plasma of active TB patients. Exosomes from all patients are mostly composed of sphingomyelins (SM), phosphatidylcholines, phosphatidylinositols, free fatty acids, triacylglycerols (TAG), and cholesterylesters. Relative proportions of, e.g., SMs and TAGs, vary depending on the disease or treatment state and could be linked to Mtb pathogenesis and dormancy. We identified three proteins of Mtb origin: DNA-directed RNA polymerase subunit beta (RpoC), Diacyglycerol O-acyltransferase (Rv2285), and Formate hydrogenase (HycE), the latter of which was discovered to be differently expressed in TBL patients. Furthermore, we discovered that Mtb infection alters the host protein composition of circulating exosomes, significantly affecting a total of 37 proteins. All TB patients had low levels of apolipoproteins, as well as the antibacterial proteins cathelicidin, Scavenger Receptor Cysteine Rich Family Member (SSC5D), and Ficolin 3 (FCN3). When compared to healthy controls, the protein profiles of PTB and TBL were substantially linked, with 14 proteins being co-regulated. However, adhesion proteins (integrins, Intercellular adhesion molecule 2 (ICAM2), CD151, Proteoglycan 4 (PRG4)) were shown to be more prevalent in PTB patients, while immunoglobulins, Complement component 1r (C1R), and Glutamate receptor-interacting protein 1 (GRIP1) were found to be more abundant in TBL patients, respectively. This study could confirm findings from previous reports and uncover novel molecular profiles not previously in focus of TB research. However, we applied a minimally invasive sampling and analysis of circulating exosomes in TB patients. Based on the findings given here, future studies into host–pathogen interactions could pave the way for the development of new vaccines and therapies.
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Biomarkers that correlate with active pulmonary tuberculosis treatment response: a systematic review and meta-analysis. J Clin Microbiol 2021; 60:e0185921. [PMID: 34911364 PMCID: PMC8849205 DOI: 10.1128/jcm.01859-21] [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] [Indexed: 11/20/2022] Open
Abstract
Current WHO recommendations for monitoring treatment response in adult pulmonary tuberculosis (TB) are sputum smear microscopy and/or culture conversion at the end of the intensive phase of treatment. These methods either have suboptimal accuracy or a long turnaround time. There is a need to identify alternative biomarkers to monitor TB treatment response. We conducted a systematic review of active pulmonary TB treatment monitoring biomarkers. We screened 9,739 articles published between 1 January 2008 and 31 December 2020, of which 77 met the inclusion criteria. When studies quantitatively reported biomarker levels, we meta-analyzed the average fold change in biomarkers from pretreatment to week 8 of treatment. We also performed a meta-analysis pooling the fold change since the previous time point collected. A total of 81 biomarkers were identified from 77 studies. Overall, these studies exhibited extensive heterogeneity with regard to TB treatment monitoring study design and data reporting. Among the biomarkers identified, C-reactive protein (CRP), interleukin-6 (IL-6), interferon gamma-induced protein 10 (IP-10), and tumor necrosis factor alpha (TNF-α) had sufficient data to analyze fold changes. All four biomarker levels decreased during the first 8 weeks of treatment relative to baseline and relative to previous time points collected. Based on limited data available, CRP, IL-6, IP-10, and TNF-α have been identified as biomarkers that should be further explored in the context of TB treatment monitoring. The extensive heterogeneity in TB treatment monitoring study design and reporting is a major barrier to evaluating the performance of novel biomarkers and tools for this use case. Guidance for designing and reporting treatment monitoring studies is urgently needed.
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