Identification of Mycobacterium tuberculosis Peptides in Serum Extracellular Vesicles from Persons with Latent Tuberculosis Infection

Identification of biomarkers for latent infection and risk of progression to tuberculosis (TB) disease are needed to better identify individuals to target for preventive therapy, predict disease risk, and potentially predict preventive therapy efficacy. Our group developed multiple reaction monitori...

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Veröffentlicht in:Journal of clinical microbiology Jg. 58; H. 6
Hauptverfasser: Mehaffy, Carolina, Kruh-Garcia, Nicole A, Graham, Barbara, Jarlsberg, Leah G, Willyerd, Charis E, Borisov, Andrey, Sterling, Timothy R, Nahid, Payam, Dobos, Karen M
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Sprache:Englisch
Veröffentlicht: United States 26.05.2020
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ISSN:1098-660X, 1098-660X
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Abstract Identification of biomarkers for latent infection and risk of progression to tuberculosis (TB) disease are needed to better identify individuals to target for preventive therapy, predict disease risk, and potentially predict preventive therapy efficacy. Our group developed multiple reaction monitoring mass spectrometry (MRM-MS) assays that detected peptides in serum extracellular vesicles from TB patients. We subsequently optimized this MRM-MS assay to selectively identify 40 peptides from 19 proteins that most commonly copurify with serum vesicles of patients with TB. Here, we used this technology to evaluate if peptides can also be detected in individuals with latent TB infection (LTBI). Serum extracellular vesicles from 74 individuals presumed to have latent infection (LTBI) based on close contact with a household member with TB or a recent tuberculin skin test (TST) conversion were included in this study. Twenty-nine samples from individuals with no evidence of TB infection by TST and no known exposure to TB were used as controls to establish a threshold to account for nonspecific/background signal. We identified at least one of the 40 peptides in 70 (95%) individuals with LTBI. A single peptide from the glutamine synthetase (GlnA1) enzyme was identified in 61/74 (82%) individuals with LTBI, suggesting peptides from proteins involved in nitrogen metabolism might be candidates for pathogen-specific biomarkers for detection of LTBI. The detection of peptides in serum extracellular vesicles from persons with LTBI represents a potential advance in the diagnosis of LTBI.
AbstractList Identification of biomarkers for latent infection and risk of progression to tuberculosis (TB) disease are needed to better identify individuals to target for preventive therapy, predict disease risk, and potentially predict preventive therapy efficacy. Our group developed multiple reaction monitoring mass spectrometry (MRM-MS) assays that detected peptides in serum extracellular vesicles from TB patients. We subsequently optimized this MRM-MS assay to selectively identify 40 peptides from 19 proteins that most commonly copurify with serum vesicles of patients with TB. Here, we used this technology to evaluate if peptides can also be detected in individuals with latent TB infection (LTBI). Serum extracellular vesicles from 74 individuals presumed to have latent infection (LTBI) based on close contact with a household member with TB or a recent tuberculin skin test (TST) conversion were included in this study. Twenty-nine samples from individuals with no evidence of TB infection by TST and no known exposure to TB were used as controls to establish a threshold to account for nonspecific/background signal. We identified at least one of the 40 peptides in 70 (95%) individuals with LTBI. A single peptide from the glutamine synthetase (GlnA1) enzyme was identified in 61/74 (82%) individuals with LTBI, suggesting peptides from proteins involved in nitrogen metabolism might be candidates for pathogen-specific biomarkers for detection of LTBI. The detection of peptides in serum extracellular vesicles from persons with LTBI represents a potential advance in the diagnosis of LTBI.
Identification of biomarkers for latent Mycobacterium tuberculosis infection and risk of progression to tuberculosis (TB) disease are needed to better identify individuals to target for preventive therapy, predict disease risk, and potentially predict preventive therapy efficacy. Our group developed multiple reaction monitoring mass spectrometry (MRM-MS) assays that detected M. tuberculosis peptides in serum extracellular vesicles from TB patients. We subsequently optimized this MRM-MS assay to selectively identify 40 M. tuberculosis peptides from 19 proteins that most commonly copurify with serum vesicles of patients with TB. Here, we used this technology to evaluate if M. tuberculosis peptides can also be detected in individuals with latent TB infection (LTBI). Serum extracellular vesicles from 74 individuals presumed to have latent M. tuberculosis infection (LTBI) based on close contact with a household member with TB or a recent tuberculin skin test (TST) conversion were included in this study. Twenty-nine samples from individuals with no evidence of TB infection by TST and no known exposure to TB were used as controls to establish a threshold to account for nonspecific/background signal. We identified at least one of the 40 M. tuberculosis peptides in 70 (95%) individuals with LTBI. A single peptide from the glutamine synthetase (GlnA1) enzyme was identified in 61/74 (82%) individuals with LTBI, suggesting peptides from M. tuberculosis proteins involved in nitrogen metabolism might be candidates for pathogen-specific biomarkers for detection of LTBI. The detection of M. tuberculosis peptides in serum extracellular vesicles from persons with LTBI represents a potential advance in the diagnosis of LTBI.Identification of biomarkers for latent Mycobacterium tuberculosis infection and risk of progression to tuberculosis (TB) disease are needed to better identify individuals to target for preventive therapy, predict disease risk, and potentially predict preventive therapy efficacy. Our group developed multiple reaction monitoring mass spectrometry (MRM-MS) assays that detected M. tuberculosis peptides in serum extracellular vesicles from TB patients. We subsequently optimized this MRM-MS assay to selectively identify 40 M. tuberculosis peptides from 19 proteins that most commonly copurify with serum vesicles of patients with TB. Here, we used this technology to evaluate if M. tuberculosis peptides can also be detected in individuals with latent TB infection (LTBI). Serum extracellular vesicles from 74 individuals presumed to have latent M. tuberculosis infection (LTBI) based on close contact with a household member with TB or a recent tuberculin skin test (TST) conversion were included in this study. Twenty-nine samples from individuals with no evidence of TB infection by TST and no known exposure to TB were used as controls to establish a threshold to account for nonspecific/background signal. We identified at least one of the 40 M. tuberculosis peptides in 70 (95%) individuals with LTBI. A single peptide from the glutamine synthetase (GlnA1) enzyme was identified in 61/74 (82%) individuals with LTBI, suggesting peptides from M. tuberculosis proteins involved in nitrogen metabolism might be candidates for pathogen-specific biomarkers for detection of LTBI. The detection of M. tuberculosis peptides in serum extracellular vesicles from persons with LTBI represents a potential advance in the diagnosis of LTBI.
Author Mehaffy, Carolina
Graham, Barbara
Jarlsberg, Leah G
Nahid, Payam
Sterling, Timothy R
Dobos, Karen M
Kruh-Garcia, Nicole A
Willyerd, Charis E
Borisov, Andrey
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  givenname: Carolina
  surname: Mehaffy
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  organization: Proteomic and Metabolomics Facility, Colorado State University, Fort Collins, Colorado, USA
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  givenname: Nicole A
  surname: Kruh-Garcia
  fullname: Kruh-Garcia, Nicole A
  organization: Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, Colorado, USA
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  surname: Graham
  fullname: Graham, Barbara
  organization: Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, Colorado, USA
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  givenname: Leah G
  surname: Jarlsberg
  fullname: Jarlsberg, Leah G
  organization: Division of Pulmonary and Critical Care Medicine, University of California San Francisco, Zuckerberg San Francisco General, San Francisco, California, USA
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  surname: Willyerd
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  organization: Clinical Data Science Associates, LLC, Fort Collins, Colorado, USA
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  organization: Division of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
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  organization: Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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  givenname: Payam
  surname: Nahid
  fullname: Nahid, Payam
  organization: Division of Pulmonary and Critical Care Medicine, University of California San Francisco, Zuckerberg San Francisco General, San Francisco, California, USA
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  givenname: Karen M
  orcidid: 0000-0001-7115-8524
  surname: Dobos
  fullname: Dobos, Karen M
  email: Karen.Dobos@colostate.edu
  organization: Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, Colorado, USA Karen.Dobos@colostate.edu
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