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Open Access 28-09-2024 | Mycobacterium Tuberculosis | Original Research Paper

Olink proteomics and lipidomics analysis of serum from patients infected with non-tuberculous mycobacteria and Mycobacterium tuberculosis

Authors: Li Wang, Guoling Yang, Liang Guo, Lan Yao, Yidian Liu, Wei Sha

Published in: Inflammation Research | Issue 11/2024

Abstract

Background

Non-tuberculous mycobacterial (NTM) and Mycobacterium tuberculosis (MTB) infections are difficult to diagnose and treat, significantly burdening global health. The host immune status is generally believed to be associated with the onset and progression of NTM and MTB infections, but its specific impact remains unclear.

Methods

In the present study, proteomics and lipidomics analysis of serum from normal controls (n = 26) and patients with MTB (n = 26), rapidly growing NTM (RGM, n = 15), and slowly growing NTM (SGM, n = 21) were conducted using the Olink technique based on a highly sensitive and specific neighborhood extension assay and the lipidomics technique.

Results

IFN-γ, CXCL9, CXCL10, CXCL11, and CXCL13, etc. were simultaneously upregulated in MTB, RGM, and SGM, while lipids FAHFA 22:3, FAHFA 26:4, FAHFA 24:4, FAHFA 20:5, FAHFA 18:2 simultaneously downregulated. IL8, CCL3, CXCL5, and MCP-2, etc. were simultaneously upregulated in RGM and SGM compared to MTB, as well as PCs, LPCs, PEs, and LPEs. Compared with RGM, IL7, CD27, CCL17, CXCL12, and LPC 28:7-SN2 were downregulated in SGM. Pathway analyses revealed that tuberculosis, sphingolipid signaling pathway, and adipocytokine signaling pathway were regulated at the protein level and metabolite level. Diagnostic panels comprising immune-associated proteins and lipids greatly enhance diagnostic specificity and sensitivity.

Conclusion

This integrated multi-omics analysis provides a more comprehensive understanding of the molecular landscape of NTM and MTB, which may provide molecular targets for specialized therapies.

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Title: Olink proteomics and lipidomics analysis of serum from patients infected with non-tuberculous mycobacteria and Mycobacterium tuberculosis
Authors: Li Wang
Guoling Yang
Liang Guo
Lan Yao
Yidian Liu
Wei Sha
Publication date: 28-09-2024
Publisher: Springer International Publishing
Keywords: Mycobacterium Tuberculosis
Non-Tuberculous Mycobacteria
Biomarkers
Published in: Inflammation Research / Issue 11/2024
Print ISSN: 1023-3830
Electronic ISSN: 1420-908X
DOI: https://doi.org/10.1007/s00011-024-01943-z

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Abstract

Background

Methods

Results

Conclusion

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