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.

Label-Free Quantitative Proteomics Identifies Novel Plasma Biomarkers for Distinguishing Pulmonary Tuberculosis and Latent Infection

“…Most of the previous studies on TB biomarker screening were focused on the differential analysis between active TB and the other pulmonary diseases (COPD, LC, or pneumonia), or between active TB and HC ( Liu et al, 2011 , 2013 , 2014 ; Song et al, 2014 ; Xu et al, 2014 , 2015 ). Only one study has characterized the plasma proteins in children at different M.TB infection stage (active TB and LTBI), and four proteins (XRCC4, PCF11, SEMA4A, and ATP11A) were detected and confirmed between active TB and LTBI using proteomics analysis and followed western blot analysis ( Li et al, 2017 ). However, these four proteins were not detected in our study, possibly because of the considerable difference in immune response between adults and children.…”

Pediatric Tuberculosis: The Impact of “Omics” on Diagnostics Development

“…For instance, a quantitative proteomics approach using LC-MS/MS was employed to characterize plasma from 72 children in different test groups (active TB, inflammatory disease control, and healthy control) at a Beijing Children’s Hospital. The study identified 49 proteins in pediatric cases that were differentially expressed between active and latent TB [ 72 ]. One study characterized the plasma proteins in children at different MTB infection stages (active TB and LTBI), and identified four proteins—XRCC4, PCF11, SEMA4A, and ATP11A—to be signatures of active TB disease using proteomics [ 72 ].…”

“…The study identified 49 proteins in pediatric cases that were differentially expressed between active and latent TB [ 72 ]. One study characterized the plasma proteins in children at different MTB infection stages (active TB and LTBI), and identified four proteins—XRCC4, PCF11, SEMA4A, and ATP11A—to be signatures of active TB disease using proteomics [ 72 ]. Given the differential presentation of pediatric TB disease, it is likely that a combinatorial approach exploring varied biomarker signature profiles may provide a greater reliability of identification rather than a single factor approach [ 110 ].…”

“… Representative cases for an “omics-based” approach to build a comprehensive understanding of the pathology of both adult and pediatric TB. There are still many omics-based approaches to be further investigated, especially for pediatric TB [ 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 ]. …”

Label‐Free Quantitative Proteomics Identifies Novel Biomarkers for Distinguishing Tuberculosis Pleural Effusion from Malignant Pleural Effusion

“…This technology has been widely used in identifying potential biomarkers of cancers, neurodegenerative diseases, renal transplantation, and endocrine system and metabolic diseases . Moreover, the label‐free proteomics technique has also been a promising method to discover TB‐associated protein markers in recent years . However, no study has used this technique to identify potential biomarkers for distinguishing TBPE from MPE, and no study has established a useful diagnostic model for distinguishing TBPE from MPE and further validated it in an independent blind testing set.…”