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Kotimoole CN, Ramya VK, Kaur P, Reiling N, Shandil RK, Narayanan S, Flo TH, Prasad TSK. Discovery of Species-Specific Proteotypic Peptides To Establish a Spectral Library Platform for Identification of Nontuberculosis Mycobacteria from Mass Spectrometry-Based Proteomics. J Proteome Res 2024; 23:1102-1117. [PMID: 38358903 DOI: 10.1021/acs.jproteome.3c00850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/17/2024]
Abstract
Nontuberculous mycobacteria are opportunistic bacteria pulmonary and extra-pulmonary infections in humans that closely resemble Mycobacterium tuberculosis. Although genome sequencing strategies helped determine NTMs, a common assay for the detection of coinfection by multiple NTMs with M. tuberculosis in the primary attempt of diagnosis is still elusive. Such a lack of efficiency leads to delayed therapy, an inappropriate choice of drugs, drug resistance, disease complications, morbidity, and mortality. Although a high-resolution LC-MS/MS-based multiprotein panel assay can be developed due to its specificity and sensitivity, it needs a library of species-specific peptides as a platform. Toward this, we performed an analysis of proteomes of 9 NTM species with more than 20 million peptide spectrum matches gathered from 26 proteome data sets. Our metaproteomic analyses determined 48,172 species-specific proteotypic peptides across 9 NTMs. Notably, M. smegmatis (26,008), M. abscessus (12,442), M. vaccae (6487), M. fortuitum (1623), M. avium subsp. paratuberculosis (844), M. avium subsp. hominissuis (580), and M. marinum (112) displayed >100 species-specific proteotypic peptides. Finally, these peptides and corresponding spectra have been compiled into a spectral library, FASTA, and JSON formats for future reference and validation in clinical cohorts by the biomedical community for further translation.
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Affiliation(s)
- Chinmaya Narayana Kotimoole
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore 575018, India
| | - Vadageri Krishnamurthy Ramya
- Foundation for Neglected Disease Research, 20A, KIADB Industrial Area, Veerapura Village, Doddaballapur, Bengaluru 561203, India
| | - Parvinder Kaur
- Foundation for Neglected Disease Research, 20A, KIADB Industrial Area, Veerapura Village, Doddaballapur, Bengaluru 561203, India
| | - Norbert Reiling
- Microbial Interface Biology, Research Center Borstel, Leibniz Lung Center, Parkallee 22, D-23845 Borstel, Germany
- German Center for Infection Research (DZIF), Site Hamburg-Lübeck-Borstel-Riems, 23845 Borstel, Germany
| | - Radha Krishan Shandil
- Foundation for Neglected Disease Research, 20A, KIADB Industrial Area, Veerapura Village, Doddaballapur, Bengaluru 561203, India
| | - Shridhar Narayanan
- Foundation for Neglected Disease Research, 20A, KIADB Industrial Area, Veerapura Village, Doddaballapur, Bengaluru 561203, India
| | - Trude Helen Flo
- Centre of Molecular Inflammation Research, Department of Clinical and Molecular Medicine Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Kunnskapssenteret, Øya 424.04.035, Norway
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Kotimoole C, Antil N, Kasaragod S, Behera S, Arvind A, Reiling N, Flo T, Prasad T. Development of a spectral library for the discovery of altered genomic events in Mycobacterium avium associated with virulence using mass spectrometry-based proteogenomic analysis. Mol Cell Proteomics 2023; 22:100533. [PMID: 36948415 PMCID: PMC10149365 DOI: 10.1016/j.mcpro.2023.100533] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 02/02/2023] [Accepted: 03/16/2023] [Indexed: 03/24/2023] Open
Abstract
Mycobacterium avium is one of the prominent disease-causing bacteria in humans. It causes lymphadenitis, chronic and extrapulmonary, and disseminated infections in adults, children, and immunocompromised patients. M. avium has ∼4,500 predicted protein-coding regions on average, which can help discover several variants at the proteome level. Many of them are potentially associated with virulence; thus, identifying such proteins can be a helpful feature in developing panel-based theranostics. In line with such a long-term goal, we carried out an in-depth proteomic analysis of M. avium with both data-dependent and data-independent acquisition methods. Further, a set of proteogenomic investigations were carried out using i) a protein database for Mycobacterium tuberculosis, ii) a M. avium genome six-frame translated database, and iii) a variant protein database of M. avium. A search of mass spectrometry data against M. avium protein database resulted in identifying 2,954 proteins. Further, proteogenomic analyses aided in identifying 1,301 novel peptide sequences and correcting translation start sites for 15 proteins. Ultimately, we created a spectral library of M. avium proteins, including novel genome search-specific peptides and variant peptides detected in this study. We validated the spectral library by a data-independent acquisition of the M. avium proteome. Thus, we present an M. avium spectral library of 29,033 peptide precursors supported by 0.4 million fragment ions for further use by the biomedical community.
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Affiliation(s)
- ChinmayaNarayana Kotimoole
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore, 575018, India
| | - Neelam Antil
- Institute of Bioinformatics, International Technology Park, Bangalore, India
| | - Sandeep Kasaragod
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore, 575018, India
| | - SantoshKumar Behera
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore, 575018, India
| | - Anjana Arvind
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore, 575018, India
| | - Norbert Reiling
- Microbial Interface Biology, Research Center Borstel, Leibniz Lung Center, Parkallee 22, D-23845 Borstel, Germany; German Center for Infection Research (DZIF), Site Hamburg-Lübeck-Borstel-Riems, 23845 Borstel, Germany
| | - TrudeHelen Flo
- Centre of Molecular Inflammation Research, Department of Clinical and Molecular Medicine Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Kunnskapssenteret, 424.04.035, Øya, Norway
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Chen H, Li S, Zhao W, Deng J, Yan Z, Zhang T, Wen SA, Guo H, Li L, Yuan J, Zhang H, Ma L, Zheng J, Gao M, Pang Y. A Peptidomic Approach to Identify Novel Antigen Biomarkers for the Diagnosis of Tuberculosis. Infect Drug Resist 2022; 15:4617-4626. [PMID: 36003990 PMCID: PMC9394730 DOI: 10.2147/idr.s373652] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 08/01/2022] [Indexed: 11/23/2022] Open
Abstract
Background Here, we conducted a peptidomic study in murine model to identify novel antigen biomarkers for the diagnosis of tuberculosis (TB) with improved performance. Methods Four recombinant proteins, including Mycobacterium tuberculosis protein 32 (MPT32), Mycobacterium tuberculosis protein 64 (MPT64), culture filtrate protein 10 (CFP10), and phosphate ABC transporter substrate-binding lipoprotein (PstS1) were expressed and intravenously injected into BALB/c mice. The serum were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The concentrations of candidate peptides in serum of suspected TB patients were determined using competitive enzyme-linked immunosorbent assay. Results A total of 65 peptides from 4 MTB precursor recombinant proteins were identified in mouse serum by LC-MS/MS, of which 5 peptides were selected as candidates for serological analysis. The concentrations of peptides MPT64-2, CFP10-2 and PstS1-2 in TB patients were significantly higher than those in non-TB patients. MPT64-2 exhibited the most promising sensitivity (81.4%), followed by PstS1-2 and CFP10-2. In addition, PstS1-2 had the highest specificity (93.3%), followed by CFP10-2 and MPT64-2. According to the area under the curve (AUC), MPT64-2 (AUC = 0.863), PstS1-2 (AUC = 0.812) and CFP10-2 (AUC = 0.809) exhibited better diagnostic validity. Conclusion We develop an effective approach to identify new antigen biomarkers via LC-MS/MS-based peptidomics. Multiple peptides exhibit promising efficacy in diagnosis of active TB patients.
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Affiliation(s)
- Hongmei Chen
- Department of Tuberculosis, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, People's Republic of China
| | - Shanshan Li
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, People's Republic of China
| | - Weijie Zhao
- Clinical Trial Agency Office, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, People's Republic of China
| | - Jiaheng Deng
- Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, and Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China
| | - Zhuohong Yan
- Department of Central Laboratory, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, People's Republic of China
| | - Tingting Zhang
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, People's Republic of China
| | - Shu' An Wen
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, People's Republic of China
| | - Haiping Guo
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, People's Republic of China
| | - Lei Li
- Electral Safety Research & Development Center, Beijing Normal University, Zhuhai, People's Republic of China
| | - Jianfeng Yuan
- Electral Safety Research & Development Center, Beijing Normal University, Zhuhai, People's Republic of China
| | - Hongtao Zhang
- Department of Central Laboratory, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, People's Republic of China
| | - Liping Ma
- Department of Tuberculosis, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, People's Republic of China
| | - Jianhua Zheng
- Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, and Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China
| | - Mengqiu Gao
- Department of Tuberculosis, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, People's Republic of China
| | - Yu Pang
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, People's Republic of China
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Liu L, Deng J, Yang Q, Wei C, Liu B, Zhang H, Xin H, Pan S, Liu Z, Wang D, Pang Y, Chen X, Gao L, Zheng J, Liu R, Jin Q. Urinary proteomic analysis to identify a potential protein biomarker panel for the diagnosis of tuberculosis. IUBMB Life 2021; 73:1073-1083. [PMID: 34048129 DOI: 10.1002/iub.2509] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 05/17/2021] [Accepted: 05/19/2021] [Indexed: 01/06/2023]
Abstract
Tuberculosis (TB) is caused by Mycobacterium tuberculosis and is one of the primary causes of death worldwide. Rapid and accurate diagnosis of TB is one of the most direct means to reduce the incidence of TB. In this study, urinary proteomic profiling of TB patients and non-TB individual controls (HCs) was performed, and differentially expressed urinary proteins between TB and HCs were compared and exclusively expressed proteins in TB patients were selected to establish a clinically useful disease marker panel. In total, these top 11 targeted proteins with 265 peptides were scheduled for multiple reaction monitoring validation analysis by using urine samples from 52 TB patients and 52 HCs. The result demonstrated that a three-protein combination out of the five-protein panel (namely P22352, Q9P121, P15151, Q13291, and Q8NDA2) exhibited sensitivity rate of 82.7% in the diagnosis of TB. Furthermore, the three-protein combination could differentiate TB from the latent tuberculosis (LTB) effectively, which exhibited specificity rate of 92.3% for the diagnosis of TB from the LTB category. Although more numbers of clinical samples are required for further verification, the results provided preliminary evidence that this "three-protein combination" out of the five-protein panel could probably be a novel TB diagnostic biomarker in clinical application.
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Affiliation(s)
- Liguo Liu
- NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jiaheng Deng
- NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Qianting Yang
- National Clinical Research Center for Infectious Diseases, Guangdong Key Lab for Diagnosis and Treatment of Emerging Infectious Diseases, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen, China
| | - Candong Wei
- NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Bo Liu
- NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Haoran Zhang
- NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Henan Xin
- NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shouguo Pan
- Center for Diseases Control and Prevention of Zhongmu County, Zhongmu, China
| | - Zisen Liu
- Center for Diseases Control and Prevention of Zhongmu County, Zhongmu, China
| | - Dakuan Wang
- Center for Diseases Control and Prevention of Zhongmu County, Zhongmu, China
| | - Yu Pang
- Department of Tuberculosis, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Xinchun Chen
- Department of Pathogen Biology, Shenzhen University School of Medicine, Shenzhen, China
| | - Lei Gao
- NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jianhua Zheng
- NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Rongmei Liu
- Department of Tuberculosis, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Qi Jin
- NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Deng J, Liu L, Yang Q, Wei C, Zhang H, Xin H, Pan S, Liu Z, Wang D, Liu B, Gao L, Liu R, Pang Y, Chen X, Zheng J, Jin Q. Urinary metabolomic analysis to identify potential markers for the diagnosis of tuberculosis and latent tuberculosis. Arch Biochem Biophys 2021; 704:108876. [PMID: 33864753 DOI: 10.1016/j.abb.2021.108876] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Revised: 04/07/2021] [Accepted: 04/08/2021] [Indexed: 11/24/2022]
Abstract
Tuberculosis (TB) is a serious infectious disease with high infection and mortality rates. 5%-10% of the latent tuberculosis infections (LTBI) are likely to develop into active TB, and there are currently no clinical biomarkers that can distinguish between LTBI, active TB and other non-tuberculosis populations. Therefore, it is necessary to develop rapid diagnostic methods for active TB and LTBI. In this study, urinary metabolome of 30 active TB samples and the same number of LTBI and non-TB control samples were identified and analyzed by UPLC-Q Exactive MS. In total, 3744 metabolite components were obtained in ESI- mode and 4086 in ESI + mode. Orthogonal partial least square discriminant analysis (OPLS-DA) and hierarchical cluster analysis (HCA) showed that there were significant differences among LTBI, active TB and non-TB. Six differential metabolites were screened in positive and negative mode, 3-hexenoic acid, glutathione (GSH), glycochenodeoxycholate-3-sulfate, N-[4'-hydroxy-(E)-cinnamoyl]-l-aspartic acid, deoxyribose 5-phosphate and histamine. The overlapping pathways differential metabolites involved were mainly related to immune regulation and urea cycle. The results showed that the urine metabolism of TB patients was disordered and many metabolic pathways changed. Multivariate statistical analysis revealed that GSH and histamine were selected as potential molecular markers, with area under curve of receiver operating characteristic curve over 0.75. Among the multiple differential metabolites, GSH and histamine changed to varying degrees in active TB, LTBI and the non-TB control group. The levels of GSH and histamine in 48 urinary samples were measured by ELISA in validation phase, and the result in our study provided the potential for non-invasive biomarkers of TB.
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Affiliation(s)
- Jiaheng Deng
- NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, and Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Liguo Liu
- NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, and Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Qianting Yang
- National Clinical Research Center for Infectious Diseases, Guangdong Key Lab for Diagnosis & Treatment of Emerging Infectious Diseases, Shenzhen Third People's Hospital, Southern University of Science and Technology, Shenzhen, 518112, China
| | - Candong Wei
- NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, and Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Haoran Zhang
- NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, and Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Henan Xin
- NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, and Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Shouguo Pan
- Center for Diseases Control and Prevention of Zhongmu County, Zhongmu, 451450, China
| | - Zisen Liu
- Center for Diseases Control and Prevention of Zhongmu County, Zhongmu, 451450, China
| | - Dakuan Wang
- Center for Diseases Control and Prevention of Zhongmu County, Zhongmu, 451450, China
| | - Bo Liu
- NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, and Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Lei Gao
- NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, and Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Rongmei Liu
- Department of Tuberculosis, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, No 97, Machang, Tongzhou District, Beijing, 101149, China
| | - Yu Pang
- Department of Tuberculosis, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, No 97, Machang, Tongzhou District, Beijing, 101149, China
| | - Xinchun Chen
- Department of Pathogen Biology, Shenzhen University School of Medicine, Shenzhen, 518060, China
| | - Jianhua Zheng
- NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, and Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
| | - Qi Jin
- NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, and Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
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Fijalkowska D, Fijalkowski I, Willems P, Van Damme P. Bacterial riboproteogenomics: the era of N-terminal proteoform existence revealed. FEMS Microbiol Rev 2021; 44:418-431. [PMID: 32386204 DOI: 10.1093/femsre/fuaa013] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Accepted: 05/07/2020] [Indexed: 12/17/2022] Open
Abstract
With the rapid increase in the number of sequenced prokaryotic genomes, relying on automated gene annotation became a necessity. Multiple lines of evidence, however, suggest that current bacterial genome annotations may contain inconsistencies and are incomplete, even for so-called well-annotated genomes. We here discuss underexplored sources of protein diversity and new methodologies for high-throughput genome reannotation. The expression of multiple molecular forms of proteins (proteoforms) from a single gene, particularly driven by alternative translation initiation, is gaining interest as a prominent contributor to bacterial protein diversity. In consequence, riboproteogenomic pipelines were proposed to comprehensively capture proteoform expression in prokaryotes by the complementary use of (positional) proteomics and the direct readout of translated genomic regions using ribosome profiling. To complement these discoveries, tailored strategies are required for the functional characterization of newly discovered bacterial proteoforms.
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Affiliation(s)
- Daria Fijalkowska
- Department of Biochemistry and Microbiology, Ghent University, K. L. Ledeganckstraat 35, B-9000 Ghent, Belgium
| | - Igor Fijalkowski
- Department of Biochemistry and Microbiology, Ghent University, K. L. Ledeganckstraat 35, B-9000 Ghent, Belgium
| | - Patrick Willems
- Department of Biochemistry and Microbiology, Ghent University, K. L. Ledeganckstraat 35, B-9000 Ghent, Belgium
| | - Petra Van Damme
- Department of Biochemistry and Microbiology, Ghent University, K. L. Ledeganckstraat 35, B-9000 Ghent, Belgium
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Gong WP, Liang Y, Ling YB, Zhang JX, Yang YR, Wang L, Wang J, Shi YC, Wu XQ. Effects of Mycobacterium vaccae vaccine in a mouse model of tuberculosis: protective action and differentially expressed genes. Mil Med Res 2020; 7:25. [PMID: 32493477 PMCID: PMC7268289 DOI: 10.1186/s40779-020-00258-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2019] [Accepted: 05/18/2020] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Tuberculosis is a leading cause of death worldwide. BCG is an effective vaccine, but not widely used in many parts of the world due to a variety of issues. Mycobacterium vaccae (M. vaccae) is another vaccine used in human subjects to prevent tuberculosis. In the current study, we investigated the potential mechanisms of M. vaccae vaccination by determining differentially expressed genes in mice infected with M. tuberculosis before and after M. vaccae vaccination. METHODS Three days after exposure to M. tuberculosis H37Rv strain (5 × 105 CFU), adult BALB/c mice randomly received either M. vaccae vaccine (22.5 μg) or vehicle via intramuscular injection (n = 8). Booster immunization was conducted 14 and 28 days after the primary immunization. Differentially expressed genes were identified by microarray followed by standard bioinformatics analysis. RESULTS M. vaccae vaccination provided protection against M. tuberculosis infection (most prominent in the lungs). We identified 2326 upregulated and 2221 downregulated genes in vaccinated mice. These changes could be mapped to a total of 123 signaling pathways (68 upregulated and 55 downregulated). Further analysis pinpointed to the MyD88-dependent TLR signaling pathway and PI3K-Akt signaling pathway as most likely to be functional. CONCLUSIONS M. vaccae vaccine provided good protection in mice against M. tuberculosis infection, via a highly complex set of molecular changes. Our findings may provide clue to guide development of more effective vaccine against tuberculosis.
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Affiliation(s)
- Wen-Ping Gong
- Army Tuberculosis Prevention and Control Key Laboratory/Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Institute for Tuberculosis Research, the 8th Medical Center of Chinese PLA General Hospital, Beijing, 100091, China
| | - Yan Liang
- Army Tuberculosis Prevention and Control Key Laboratory/Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Institute for Tuberculosis Research, the 8th Medical Center of Chinese PLA General Hospital, Beijing, 100091, China
| | - Yan-Bo Ling
- Army Tuberculosis Prevention and Control Key Laboratory/Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Institute for Tuberculosis Research, the 8th Medical Center of Chinese PLA General Hospital, Beijing, 100091, China
| | - Jun-Xian Zhang
- Army Tuberculosis Prevention and Control Key Laboratory/Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Institute for Tuberculosis Research, the 8th Medical Center of Chinese PLA General Hospital, Beijing, 100091, China
| | - You-Rong Yang
- Army Tuberculosis Prevention and Control Key Laboratory/Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Institute for Tuberculosis Research, the 8th Medical Center of Chinese PLA General Hospital, Beijing, 100091, China
| | - Lan Wang
- Army Tuberculosis Prevention and Control Key Laboratory/Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Institute for Tuberculosis Research, the 8th Medical Center of Chinese PLA General Hospital, Beijing, 100091, China
| | - Jie Wang
- Army Tuberculosis Prevention and Control Key Laboratory/Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Institute for Tuberculosis Research, the 8th Medical Center of Chinese PLA General Hospital, Beijing, 100091, China
| | - Ying-Chang Shi
- Army Tuberculosis Prevention and Control Key Laboratory/Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Institute for Tuberculosis Research, the 8th Medical Center of Chinese PLA General Hospital, Beijing, 100091, China
| | - Xue-Qiong Wu
- Army Tuberculosis Prevention and Control Key Laboratory/Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Institute for Tuberculosis Research, the 8th Medical Center of Chinese PLA General Hospital, Beijing, 100091, China.
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From six to zero per cent Mycobacterium avium subsp. paratuberculosis milk ELISA positivity in three years - probably induced by Mycobacterium vaccae. J DAIRY RES 2020; 87:204-207. [PMID: 32308162 DOI: 10.1017/s0022029920000278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
This research communication reports the results of a study aimed at investigating the effects of introducing Mycobacterium vaccae on paratuberculosis carriage in a dairy herd. M. vaccae is a non-pathogenic member of the Mycobacteriaceae, with immunomodulatory and immunotherapeutic capabilities, acting by stimulating the cellular immune system, important in protection against paratuberculosis. Starting in 2014 we administered, by gavage, 1010 live M. vaccae bacteria to all new-born heifers on a dairy farm, first within 24 h of birth and again 2 weeks later. Paratuberculosis carriage was monitored yearly by milk ELISA. Faecal samples of 50% of cows, aged 3 years, born 1, 2 or 3 years before the experiment's onset, were tested by qPCR for MAP shedding and compared to 100% treated cows of the same age. Within 3 years, milk ELISA positivity was reduced from 6 to 0% and remained unchanged for the subsequent 2 years. One qPCR positive control cow was found each year for a total of 3 animals (2.46%). One positive cow (1%) was found among the treated cows. Two of the 3 positive control animals, still present on the farm at the end of 2019, tested negative whereas the positive test cow continued shedding MAP. M. vaccae shedding heifers mixing with adult cows were the probable means of the microorganism's propagation. The results of this investigation indicate that the introduction of live M. vaccae may be an inexpensive and fast alternative to current paratuberculosis control practices, justifying further exploration of the topic.
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Phase III, placebo-controlled, randomized, double-blind trial of tableted, therapeutic TB vaccine (V7) containing heat-killed M. vaccae administered daily for one month. J Clin Tuberc Other Mycobact Dis 2019; 18:100141. [PMID: 31890902 PMCID: PMC6933248 DOI: 10.1016/j.jctube.2019.100141] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Objective Immunotherapy of tuberculosis (TB) to shorten treatment duration represents an unmet medical need. Orally delivered, tableted TB vaccine (V7) containing heat-killed Mycobacterium vaccae (NCTC 11659) has been demonstrated in prior clinical studies to be safe and fast-acting immune adjunct. Methods The outcome of Phase III trial of V7 containing 10 µg of hydrolyzed M. vaccae was evaluated in 152 patients randomized at 2:1 ratio: V7 (N = 100), placebo (N = 52). Both arms received conventional 1st or 2nd line TB drugs co-administered with daily pill of V7 or placebo. Results After one month mycobacterial clearance was observed in 68% (P < 0.0001) and 23.1% (P = 0.04) of patients on V7 and placebo. Stratified conversion rates in V7 recipients with drug-sensitive and multidrug-resistant TB were 86.7% and 55.6% vs 27.2% and 15% in placebo. Patients on V7 gained on average 2.4 kg (P < 0.0001) vs 0.3 kg (P = 0.18) in placebo. Improvements in hemoglobin levels, erythrocyte sedimentation rate and leukocyte counts were significantly better than in controls. Liver function tests revealed that V7 can prevent chemotherapy-induced hepatic damage. Conclusion Oral M. vaccae is safe, can overcome TB-associated weight loss and inflammation, reduce hepatotoxicity of TB drugs, improve sputum conversion three-fold OR 3.15; 95%CI (2.3,4.6), and cut treatment length by at least six-fold. Longer follow-up studies might be needed to further substantiate our findings (Clinicaltrials.gov: NCT01977768).
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Advani J, Verma R, Chatterjee O, Devasahayam Arokia Balaya R, Najar MA, Ravishankara N, Suresh S, Pachori PK, Gupta UD, Pinto SM, Chauhan DS, Tripathy SP, Gowda H, Prasad TK. Rise of Clinical Microbial Proteogenomics: A Multiomics Approach to Nontuberculous Mycobacterium—The Case ofMycobacterium abscessusUC22. ACTA ACUST UNITED AC 2019; 23:1-16. [DOI: 10.1089/omi.2018.0116] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Affiliation(s)
- Jayshree Advani
- Institute of Bioinformatics, International Technology Park, Bangalore, India
- Manipal Academy of Higher Education, Manipal, India
| | - Renu Verma
- Institute of Bioinformatics, International Technology Park, Bangalore, India
| | - Oishi Chatterjee
- Institute of Bioinformatics, International Technology Park, Bangalore, India
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore, India
- School of Biotechnology, Amrita Vishwa Vidyapeetham, Kollam, India
| | - Rex Devasahayam Arokia Balaya
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore, India
| | - Mohd Altaf Najar
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore, India
| | - Namitha Ravishankara
- Department of Biotechnology, M.S. Ramaiah Institute of Technology, Bangalore, India
| | - Sneha Suresh
- Department of Biotechnology, M.S. Ramaiah Institute of Technology, Bangalore, India
| | - Praveen Kumar Pachori
- Department of Microbiology and Molecular Biology, ICMR-National JALMA Institute for Leprosy & Other Mycobacterial Diseases, Agra, India
| | - Umesh D. Gupta
- Department of Microbiology and Molecular Biology, ICMR-National JALMA Institute for Leprosy & Other Mycobacterial Diseases, Agra, India
| | - Sneha M. Pinto
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore, India
| | - Devendra S. Chauhan
- Department of Microbiology and Molecular Biology, ICMR-National JALMA Institute for Leprosy & Other Mycobacterial Diseases, Agra, India
| | - Srikanth Prasad Tripathy
- Department of Microbiology and Molecular Biology, ICMR-National JALMA Institute for Leprosy & Other Mycobacterial Diseases, Agra, India
| | - Harsha Gowda
- Institute of Bioinformatics, International Technology Park, Bangalore, India
| | - T.S. Keshava Prasad
- Institute of Bioinformatics, International Technology Park, Bangalore, India
- Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore, India
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