Identification and Validation of Genes Related to Macrophage Polarization and Cell Death Modes Under Mycobacterium tuberculosis Infection

Abstract

Purpose

To investigate the correlation between M1/M2 macrophages (M1/M2 Mφ) and cell death mode under Mycobacterium tuberculosis (Mtb) infection.

Methods

Raw gene expression profiles were collected from the Gene Expression Omnibus (GEO) database. Genes related to different cell death modes were collected from the KEGG, FerrDb and GSEA databases. The differentially expressed genes (DEGs) of the gene expression profiles were identified using the limma package in R. The intersection genes of M1/M2 Mφ with different cell death modes were obtained by the VennDiagram package. Hub genes were obtained by constructing the protein–protein interactions (PPI) network and Receiver Operating Characteristic (ROC) curve analysis. The expression of cell death modes marker genes and Hub genes were verified by Western Blot and Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR).

Results

Bioinformatics analysis was performed to screen Hub genes of Mtb-infected M1 Mφ and different cell death modes, naming NFKB1, TNF, CFLAR, TBK1, IL6, RELA, SOCS1, AIM2; Hub genes of Mtb-infected M2 Mφ and different cell death modes, naming TNF, BIRC3, MAP1LC3C, DEPTOR, UVRAG, SOCS1. Combined with experimental validation, M1 Mφ under Mtb infection showed higher expression of death (including apoptosis, autophagy, ferroptosis, and pyroptosis) genes compared to M2 Mφ and genes such as NFKB1, TNF, CFLAR, TBK1, IL6, RELA, AIM2, BIRC3, DEPTOR show differential expression.

Conclusion

NFKB1, TNF, CFLAR, TBK1, IL6, RELA, AIM2 in Mtb-infected M1 Mφ, and TNF, BIRC3, DEPTOR in Mtb-infected M2 Mφ might be used as potential diagnostic targets for TB. At early stage of Mtb infection, apoptosis, autophagy, ferroptosis, and pyroptosis occurred more significantly in M1 Mφ than that in M2 Mφ, which may contribute to the transition of Mtb-infected Mφ from M1-dominant to M2-dominant and contribute to the immune escape mechanisms of Mtb.

Keywords:

• macrophage polarization
• cell death modes
• Mycobacterium tuberculosis
• bioinformatics analysis
• biomarkers

Abbreviations

Mtb, Mycobacterium tuberculosis; Mφ, Macrophage; TB, Tuberculosis; IFN-β, Interferon-β; IL-1β, Interleukin-1 β; TNF, Tumor Necrosis Factor; PPI, Protein–Protein Interaction; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; GEO, Gene Expression Omnibus; DEGs, differentially expressed genes; ROC, Receiver Operating Characteristic; qRT-PCR, Quantitative Real-Time Polymerase Chain Reaction; COVID-19, the coronavirus disease 2019; WHO, World Health Organization; DEDRGs, differential expression of death related genes; CC, cellular component; BP, biological process; MF, molecular function; AUC, area under the curve; FBS, fetal bovine serum.

Data Sharing Statement

Data GSE5099, GSE52918, and GSE54992 were downloaded from the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/); 701 apoptosis genes were obtained from the KEGG database (https://www.kegg.jp/) and GSEA database (https://www.gsea-msigdb.org/gsea/index.jsp); 574 autophagy genes were obtained from KEGG database, GSEA database and human autophagy database (http://www.autophagy.lu/index.html); 502 ferroptosis genes were obtained from the FerrDb database (http://www.zhounan.org/ferrdb/current/); 65 pyroptosis genes were obtained from the GSEA database.

Acknowledgments

The authors would like to thank all the investigators of the GSE5099, GSE52819, and GSE54992, involved in the present study for sharing the data online and the volunteers involved in the project.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors report no conflicts of interest in this work.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (82270013, 82272348, 81572566 and 81870016), High Talent Project of Guangdong Province (2021QN02Y720), the Guangdong Basic and Applied Basic Research Foundation (2022A1515010525), Natural Science Foundation of Guangdong Province (2023A1515030195 and 2022A1515011223), Graduate Education Innovation Program Project of Guangdong Province (2022KCXTD010, 2022XSLT047 and 2022SFKC063), the Science and Technology Project of Dongguan (20211800905072), Open Research Fund of Songshan Lake Materials Laboratory (2021SLABFN10), Open Research Fund for Key Laboratory of Tropical Disease Control Sun Yat-sen University and Ministry of Education (2022kfkt01) and Youth Research Projects of Guangdong Medical University (GDMUD2022001), Discipline construction project of Guangdong Medical University (4SG22259G, 4SG23290G, 4SG23030G, 4SG23143G, 4SG22098G and 4SG23077G).