Abstract

BackgroundTuberculosis (TB) is one of the world’s most problematic infectious diseases. The pathogen Mycobacterium tuberculosis (Mtb) is contained by the immune system in people with latent TB infection (LTBI). No overt disease symptoms occur. The environmental and internal triggers leading to reactivation of TB are not well understood. Non-tuberculosis Mycobacteria (NTM) can also cause TB-like lung disease. Comparative analysis of blood plasma proteomes from subjects afflicted by these pathologies in an endemic setting may yield new differentiating biomarkers and insights into inflammatory and immunological responses to Mtb and NTM.MethodsBlood samples from 40 human subjects in a pastoral region of Ethiopia were treated with the ESAT-6/CFP-10 antigen cocktail to stimulate anti-Mtb and anti-NTM immune responses. In addition to those of active TB, LTBI, and NTM cohorts, samples from matched healthy control (HC) subjects were available. Following the generation of sample pools, proteomes were analyzed via LC-MS/MS. These experiments were also performed without antigen stimulation steps. Statistically significant differences using the Z-score method were determined and interpreted in the context of the proteins’ functions and their contributions to biological pathways.ResultsMore than 200 proteins were identified from unstimulated and stimulated plasma samples (UPSs and SPSs, respectively). Thirty-four and 64 proteins were differentially abundant with statistical significance (P < 0.05; Benjamini-Hochberg correction with an FDR < 0.05) comparing UPS and SPS proteomic data of four groups, respectively. Bioinformatics analysis of such proteins via the Gene Ontology Resource was indicative of changes in cellular and metabolic processes, responses to stimuli, and biological regulations. The m7GpppN-mRNA hydrolase was increased in abundance in the LTBI group compared to HC subjects. Charged multivesicular body protein 4a and platelet factor-4 were increased in abundance in NTM as compared to HC and decreased in abundance in NTM as compared to active TB. C-reactive protein, α-1-acid glycoprotein 1, sialic acid-binding Ig-like lectin 16, and vitamin K-dependent protein S were also increased (P < 0.05; fold changes≥2) in SPSs and UPSs comparing active TB with LTBI and NTM cases. These three proteins, connected in a STRING functional network, contribute to the acute phase response and influence blood coagulation.ConclusionPlasma proteomes are different comparing LTBI, TB, NTM and HC cohorts. The changes are augmented following prior blood immune cell stimulation with the ESAT-6/CFP-10 antigen cocktail. The results encourage larger-cohort studies to identify specific biomarkers to diagnose NTM infection, LTBI, and to predict the risk of TB reactivation.

Highlights

  • Tuberculosis (TB) is one of the world’s most problematic infectious diseases

  • Thirty-four and 64 proteins were differentially abundant with statistical significance (P < 0.05; Benjamini-Hochberg correction with an False discovery rate (FDR) < 0.05) comparing Unstimulated plasma samples (UPSs) and Stimulated plasma samples (SPSs) proteomic data of four groups, respectively

  • The m7GpppN-Messenger ribonucleic acids (mRNAs) hydrolase was increased in abundance in the latent TB infection (LTBI) group compared to healthy control (HC) subjects

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Summary

Introduction

The pathogen Mycobacterium tuberculosis (Mtb) is contained by the immune system in people with latent TB infection (LTBI). Non-tuberculosis Mycobacteria (NTM) can cause TB-like lung disease. Using blood plasma from active TB, latent TB infection (LTBI), and healthy control (HC) subjects as sample sources, shotgun proteomic comparisons may lead to new biomarkers, yield information on mechanisms underlying differences in disease outcomes and contribute to future strategies to prevent and treat TB. More rapidly measurable biomarkers that differentiate NTM from Mtb infections and corresponding diagnostic assays with high measurement sensitivity and specificity are clinically valuable. Such diagnostic tests may benefit approaches for therapeutic intervention and pathogen transmission control [8]

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