Application of multiplexed ion mobility spectrometry towards the identification of host protein signatures of treatment effect in pulmonary tuberculosis

Komal Kedia, Jason P. Wendler, Erin S. Baker, Kristin E. Burnum-Johnson, Leah G. Jarsberg, Kelly G. Stratton, Aaron T. Wright, Paul D. Piehowski, Marina A. Gritsenko, David Lewinsohn, George B. Sigal, Marc H. Weiner, Richard D. Smith, Jon M. Jacobs, Payam Nahid

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Rationale: The monitoring of TB treatments in clinical practice and clinical trials relies on traditional sputum-based culture status indicators at specific time points. Accurate, predictive, blood-based protein markers would provide a simpler and more informative view of patient health and response to treatment. Objective: We utilized sensitive, high throughput multiplexed ion mobility-mass spectrometry (IM-MS) to characterize the serum proteome of TB patients at the start of and at 8 weeks of rifamycin-based treatment. We sought to identify treatment specific signatures within patients as well as correlate the proteome signatures to various clinical markers of treatment efficacy. Methods: Serum samples were collected from 289 subjects enrolled in CDC TB Trials Consortium Study 29 at time of enrollment and at the end of the intensive phase (after 40 doses of TB treatment). Serum proteins were immunoaffinity-depleted of high abundant components, digested to peptides and analyzed for data acquisition utilizing a unique liquid chromatography IM-MS platform (LC-IM-MS). Linear mixed models were utilized to identify serum protein changes in the host response to antibiotic treatment as well as correlations with culture status end points. Results: A total of 10,137 peptides corresponding to 872 proteins were identified, quantified, and used for statistical analysis across the longitudinal patient cohort. In response to TB treatment, 244 proteins were significantly altered. Pathway/network comparisons helped visualize the interconnected proteins, identifying up regulated (lipid transport, coagulation cascade, endopeptidase activity) and down regulated (acute phase) processes and pathways in addition to other cross regulated networks (inflammation, cell adhesion, extracellular matrix). Detection of possible lung injury serum proteins such as HPSE, significantly downregulated upon treatment. Analyses of microbiologic data over time identified a core set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2) which change in response to treatment and also strongly correlate with culture status. A similar set of proteins at baseline were found to be predictive of week 6 and 8 culture status. Conclusion: A comprehensive host serum protein dataset reflective of TB treatment effect is defined. A repeating set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2, among others) were found to change significantly in response to treatment, to strongly correlate with culture status, and at baseline to be predictive of future culture conversion. If validated in cohorts with long term follow-up to capture failure and relapse of TB, these protein markers could be developed for monitoring of treatment in clinical trials and in patient care.

Original languageEnglish (US)
Pages (from-to)52-61
Number of pages10
JournalTuberculosis
Volume112
DOIs
StatePublished - Sep 1 2018

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Pulmonary Tuberculosis
Spectrum Analysis
Ions
Blood Proteins
Proteins
Therapeutics
Proteome
Mass Spectrometry
Clinical Trials
Endopeptidases
Peptides
Lung Injury
Centers for Disease Control and Prevention (U.S.)
Sputum
Serum
Cell Adhesion
Liquid Chromatography
Extracellular Matrix
Linear Models
Patient Care

Keywords

  • Antibiotic treatment
  • Ion mobility spectrometry
  • Proteomics
  • Tuberculosis

ASJC Scopus subject areas

  • Microbiology
  • Immunology
  • Microbiology (medical)
  • Infectious Diseases

Cite this

Application of multiplexed ion mobility spectrometry towards the identification of host protein signatures of treatment effect in pulmonary tuberculosis. / Kedia, Komal; Wendler, Jason P.; Baker, Erin S.; Burnum-Johnson, Kristin E.; Jarsberg, Leah G.; Stratton, Kelly G.; Wright, Aaron T.; Piehowski, Paul D.; Gritsenko, Marina A.; Lewinsohn, David; Sigal, George B.; Weiner, Marc H.; Smith, Richard D.; Jacobs, Jon M.; Nahid, Payam.

In: Tuberculosis, Vol. 112, 01.09.2018, p. 52-61.

Research output: Contribution to journalArticle

Kedia, K, Wendler, JP, Baker, ES, Burnum-Johnson, KE, Jarsberg, LG, Stratton, KG, Wright, AT, Piehowski, PD, Gritsenko, MA, Lewinsohn, D, Sigal, GB, Weiner, MH, Smith, RD, Jacobs, JM & Nahid, P 2018, 'Application of multiplexed ion mobility spectrometry towards the identification of host protein signatures of treatment effect in pulmonary tuberculosis', Tuberculosis, vol. 112, pp. 52-61. https://doi.org/10.1016/j.tube.2018.07.005
Kedia, Komal ; Wendler, Jason P. ; Baker, Erin S. ; Burnum-Johnson, Kristin E. ; Jarsberg, Leah G. ; Stratton, Kelly G. ; Wright, Aaron T. ; Piehowski, Paul D. ; Gritsenko, Marina A. ; Lewinsohn, David ; Sigal, George B. ; Weiner, Marc H. ; Smith, Richard D. ; Jacobs, Jon M. ; Nahid, Payam. / Application of multiplexed ion mobility spectrometry towards the identification of host protein signatures of treatment effect in pulmonary tuberculosis. In: Tuberculosis. 2018 ; Vol. 112. pp. 52-61.
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abstract = "Rationale: The monitoring of TB treatments in clinical practice and clinical trials relies on traditional sputum-based culture status indicators at specific time points. Accurate, predictive, blood-based protein markers would provide a simpler and more informative view of patient health and response to treatment. Objective: We utilized sensitive, high throughput multiplexed ion mobility-mass spectrometry (IM-MS) to characterize the serum proteome of TB patients at the start of and at 8 weeks of rifamycin-based treatment. We sought to identify treatment specific signatures within patients as well as correlate the proteome signatures to various clinical markers of treatment efficacy. Methods: Serum samples were collected from 289 subjects enrolled in CDC TB Trials Consortium Study 29 at time of enrollment and at the end of the intensive phase (after 40 doses of TB treatment). Serum proteins were immunoaffinity-depleted of high abundant components, digested to peptides and analyzed for data acquisition utilizing a unique liquid chromatography IM-MS platform (LC-IM-MS). Linear mixed models were utilized to identify serum protein changes in the host response to antibiotic treatment as well as correlations with culture status end points. Results: A total of 10,137 peptides corresponding to 872 proteins were identified, quantified, and used for statistical analysis across the longitudinal patient cohort. In response to TB treatment, 244 proteins were significantly altered. Pathway/network comparisons helped visualize the interconnected proteins, identifying up regulated (lipid transport, coagulation cascade, endopeptidase activity) and down regulated (acute phase) processes and pathways in addition to other cross regulated networks (inflammation, cell adhesion, extracellular matrix). Detection of possible lung injury serum proteins such as HPSE, significantly downregulated upon treatment. Analyses of microbiologic data over time identified a core set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2) which change in response to treatment and also strongly correlate with culture status. A similar set of proteins at baseline were found to be predictive of week 6 and 8 culture status. Conclusion: A comprehensive host serum protein dataset reflective of TB treatment effect is defined. A repeating set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2, among others) were found to change significantly in response to treatment, to strongly correlate with culture status, and at baseline to be predictive of future culture conversion. If validated in cohorts with long term follow-up to capture failure and relapse of TB, these protein markers could be developed for monitoring of treatment in clinical trials and in patient care.",
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T1 - Application of multiplexed ion mobility spectrometry towards the identification of host protein signatures of treatment effect in pulmonary tuberculosis

AU - Kedia, Komal

AU - Wendler, Jason P.

AU - Baker, Erin S.

AU - Burnum-Johnson, Kristin E.

AU - Jarsberg, Leah G.

AU - Stratton, Kelly G.

AU - Wright, Aaron T.

AU - Piehowski, Paul D.

AU - Gritsenko, Marina A.

AU - Lewinsohn, David

AU - Sigal, George B.

AU - Weiner, Marc H.

AU - Smith, Richard D.

AU - Jacobs, Jon M.

AU - Nahid, Payam

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N2 - Rationale: The monitoring of TB treatments in clinical practice and clinical trials relies on traditional sputum-based culture status indicators at specific time points. Accurate, predictive, blood-based protein markers would provide a simpler and more informative view of patient health and response to treatment. Objective: We utilized sensitive, high throughput multiplexed ion mobility-mass spectrometry (IM-MS) to characterize the serum proteome of TB patients at the start of and at 8 weeks of rifamycin-based treatment. We sought to identify treatment specific signatures within patients as well as correlate the proteome signatures to various clinical markers of treatment efficacy. Methods: Serum samples were collected from 289 subjects enrolled in CDC TB Trials Consortium Study 29 at time of enrollment and at the end of the intensive phase (after 40 doses of TB treatment). Serum proteins were immunoaffinity-depleted of high abundant components, digested to peptides and analyzed for data acquisition utilizing a unique liquid chromatography IM-MS platform (LC-IM-MS). Linear mixed models were utilized to identify serum protein changes in the host response to antibiotic treatment as well as correlations with culture status end points. Results: A total of 10,137 peptides corresponding to 872 proteins were identified, quantified, and used for statistical analysis across the longitudinal patient cohort. In response to TB treatment, 244 proteins were significantly altered. Pathway/network comparisons helped visualize the interconnected proteins, identifying up regulated (lipid transport, coagulation cascade, endopeptidase activity) and down regulated (acute phase) processes and pathways in addition to other cross regulated networks (inflammation, cell adhesion, extracellular matrix). Detection of possible lung injury serum proteins such as HPSE, significantly downregulated upon treatment. Analyses of microbiologic data over time identified a core set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2) which change in response to treatment and also strongly correlate with culture status. A similar set of proteins at baseline were found to be predictive of week 6 and 8 culture status. Conclusion: A comprehensive host serum protein dataset reflective of TB treatment effect is defined. A repeating set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2, among others) were found to change significantly in response to treatment, to strongly correlate with culture status, and at baseline to be predictive of future culture conversion. If validated in cohorts with long term follow-up to capture failure and relapse of TB, these protein markers could be developed for monitoring of treatment in clinical trials and in patient care.

AB - Rationale: The monitoring of TB treatments in clinical practice and clinical trials relies on traditional sputum-based culture status indicators at specific time points. Accurate, predictive, blood-based protein markers would provide a simpler and more informative view of patient health and response to treatment. Objective: We utilized sensitive, high throughput multiplexed ion mobility-mass spectrometry (IM-MS) to characterize the serum proteome of TB patients at the start of and at 8 weeks of rifamycin-based treatment. We sought to identify treatment specific signatures within patients as well as correlate the proteome signatures to various clinical markers of treatment efficacy. Methods: Serum samples were collected from 289 subjects enrolled in CDC TB Trials Consortium Study 29 at time of enrollment and at the end of the intensive phase (after 40 doses of TB treatment). Serum proteins were immunoaffinity-depleted of high abundant components, digested to peptides and analyzed for data acquisition utilizing a unique liquid chromatography IM-MS platform (LC-IM-MS). Linear mixed models were utilized to identify serum protein changes in the host response to antibiotic treatment as well as correlations with culture status end points. Results: A total of 10,137 peptides corresponding to 872 proteins were identified, quantified, and used for statistical analysis across the longitudinal patient cohort. In response to TB treatment, 244 proteins were significantly altered. Pathway/network comparisons helped visualize the interconnected proteins, identifying up regulated (lipid transport, coagulation cascade, endopeptidase activity) and down regulated (acute phase) processes and pathways in addition to other cross regulated networks (inflammation, cell adhesion, extracellular matrix). Detection of possible lung injury serum proteins such as HPSE, significantly downregulated upon treatment. Analyses of microbiologic data over time identified a core set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2) which change in response to treatment and also strongly correlate with culture status. A similar set of proteins at baseline were found to be predictive of week 6 and 8 culture status. Conclusion: A comprehensive host serum protein dataset reflective of TB treatment effect is defined. A repeating set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2, among others) were found to change significantly in response to treatment, to strongly correlate with culture status, and at baseline to be predictive of future culture conversion. If validated in cohorts with long term follow-up to capture failure and relapse of TB, these protein markers could be developed for monitoring of treatment in clinical trials and in patient care.

KW - Antibiotic treatment

KW - Ion mobility spectrometry

KW - Proteomics

KW - Tuberculosis

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