Characterization of plasma proteins in children of different Mycobacterium tuberculosis infection status using label-free quantitative proteomics

Abstract

Tuberculosis (TB), caused by Mycobacterium tuberculosis (MTB), is an infectious disease found worldwide. Children infected with MTB are more likely to progress to active TB (ATB); however, the molecular mechanism behind this process has long been a mystery. We employed the label-free quantitative proteomic technology to identify and characterize differences in plasma proteins between ATB and latent TB infection (LTBI) in children. To detect differences that are indicative of MTB infection, we first selected proteins whose expressions were markedly different between the ATB and LTBI groups and the control groups (inflammatory disease control (IDC) and healthy control (HC) groups). A total of 521 proteins differed (> 1.5-fold or < 0.6-fold) in the LTBI group, and 318 proteins in the ATB group when compared with the control groups. Of these, 49 overlapping proteins were differentially expressed between LTBI and ATB. Gene Ontology (GO) analysis revealed most proteins had a cellular and organelle distribution. The MTB infection status was mainly related to differences in binding, cellular and metabolic processes. XRCC4, PCF11, SEMA4A and ATP11A were selected and further verified by qPCR and western blot. At the mRNA level, the expression of XRCC4, PCF11and SEMA4A presented an increased trend in ATB group compare with LTBI. At the protein level, the expression of all these proteins by western blot in ATB/LTBI was consistent with the trends from proteomic detection. Our results provide important data for future mechanism studies and biomarker selection for MTB infection in children.

Keywords: active tuberculosis (ATB); children; label-free quantitative proteomics; latent TB infection (LTBI); plasma proteins.

Figure 1. Different proteins selected through LC-MS/MS analysis

(A) 318 proteins were significantly different in ATB subjects compared with the HC and IDC groups. (B) 521 proteins were significantly different in LTBI subjects compared with the HC and IDC groups. (C) Among these protein, 49 proteins were markedly different between ATB and LTBI. (D) 41 proteins were up-regulated (>1.5 fold) and 8 proteins were down-regulated (< 0.6-fold) in the ATB group compared with the LTBI group.

Figure 2. Heat map and volcano plot of the 49 identified proteins

(A) The most striking area of up-regulation in ATB patients is seen in the region where a series of protein peaks are shown in red. (B) Important features selected by volcano plot.

Figure 3. Web Gene Ontology Annotation Plot (WEGO) classification of differentially expressed proteins by label-free quantitative proteomics experiments between ATB and LTBI

The differentially expressed proteins are grouped into three hierarchically structured terms: biological process, cellular component, and molecular function.

Figure 4. KEGG enrichment analysis of the differentially expressed proteins

Figure 5. Verification of up- or down-regulated proteins between ATB and LTBI

(A) RT-PCR analysis data of four selected proteins in the PBMCs of ATB patients compared with that of LTBI patients (n_ATB = 28, n_LTBI = 18); data are presented as means ± SD. (B) The average signals of ATB and LTBI patients group (P < 0.05, n = 5 per group); data are presented as means ± SD. (C) Western blot analysis of the four selected proteins from ATB and LTBI subjects (n=5 per group). (D) Total protein staining by Coomassie Blue employed as the loading control.