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

Abstract

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.

Keywords: LTBI; MRM-MS; biomarker; tuberculosis.

FIG 1

Number of peptides detected in individuals with LTBI. The y axis displays the percentage of individuals with LTBI; the x axis shows the number (0 to 12) detected peptides in individuals (n).

FIG 2

Results of cluster analysis of peptide concentrations. The three clusters identified are cluster 1 (green), cluster 2 (purple), and cluster 3 (blue). (A) Correlogram showing Spearman correlation coefficients (R) where P < 0.05. Upper circles are blue to indicate positive and orange to indicate negative R, and area of the circle corresponds with R absolute value; lower circles show corresponding numeric R. (B) Dendrogram showing the results of hierarchical clustering of a distance matrix calculated as dissimilarity = 1 – R.

FIG 3

Distribution of absent, unknown, and detected peptides in the 74 study participants with LTBI. The y axis represents the frequency in which each individual peptide was detected. Orange represents absent (undetected) peptides, blue represents present (detected peptides), and red represents unknowns, i.e., peptides in which a measurement was not possible due to matrix effects.