Integrative single-cell RNA sequencing and metabolomics decipher the imbalanced lipid-metabolism in maladaptive immune responses during sepsis

Han She; Lei Tan; Yi Wang; Yuanlin Du; Yuanqun Zhou; Jun Zhang; Yunxia Du; Ningke Guo; Zhengbin Wu; Qinghui Li; Daiqin Bao; Qingxiang Mao; Yi Hu; Liangming Liu; Tao Li

doi:10.3389/fimmu.2023.1181697

Integrative single-cell RNA sequencing and metabolomics decipher the imbalanced lipid-metabolism in maladaptive immune responses during sepsis

Front Immunol. 2023 Apr 27:14:1181697. doi: 10.3389/fimmu.2023.1181697. eCollection 2023.

Authors

Han She^{1

2}, Lei Tan^{1

2}, Yi Wang^{1

2}, Yuanlin Du², Yuanqun Zhou¹, Jun Zhang², Yunxia Du^{1

2}, Ningke Guo¹, Zhengbin Wu³, Qinghui Li¹, Daiqin Bao², Qingxiang Mao², Yi Hu², Liangming Liu¹, Tao Li¹

Affiliations

¹ State Key Laboratory of Trauma, Burns and Combined Injury, Shock and Transfusion Department, Daping Hospital, Army Medical University, Chongqing, China.
² Department of Anesthesiology, Daping Hospital, Army Medical University, Chongqing, China.
³ Department of Intensive Care Unit, Daping Hospital, Army Medical University, Chongqing, China.

Abstract

Background: To identify differentially expressed lipid metabolism-related genes (DE-LMRGs) responsible for immune dysfunction in sepsis.

Methods: The lipid metabolism-related hub genes were screened using machine learning algorithms, and the immune cell infiltration of these hub genes were assessed by CIBERSORT and Single-sample GSEA. Next, the immune function of these hub genes at the single-cell level were validated by comparing multiregional immune landscapes between septic patients (SP) and healthy control (HC). Then, the support vector machine-recursive feature elimination (SVM-RFE) algorithm was conducted to compare the significantly altered metabolites critical to hub genes between SP and HC. Furthermore, the role of the key hub gene was verified in sepsis rats and LPS-induced cardiomyocytes, respectively.

Results: A total of 508 DE-LMRGs were identified between SP and HC, and 5 hub genes relevant to lipid metabolism (MAPK14, EPHX2, BMX, FCER1A, and PAFAH2) were screened. Then, we found an immunosuppressive microenvironment in sepsis. The role of hub genes in immune cells was further confirmed by the single-cell RNA landscape. Moreover, significantly altered metabolites were mainly enriched in lipid metabolism-related signaling pathways and were associated with MAPK14. Finally, inhibiting MAPK14 decreased the levels of inflammatory cytokines and improved the survival and myocardial injury of sepsis.

Conclusion: The lipid metabolism-related hub genes may have great potential in prognosis prediction and precise treatment for sepsis patients.

Keywords: lipid-metabolism; machine learning algorithm; metabolomics; sepsis; single-cell RNA sequencing.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Animals
Immunity
Lipids
Metabolomics
Mitogen-Activated Protein Kinase 14*
Rats
Sepsis* / genetics
Sequence Analysis, RNA

Substances

Mitogen-Activated Protein Kinase 14
Lipids

Grants and funding

This study was supported by the Key Program of the National Natural Science Foundation of China (No.81730059) and the Key Program of the National Natural Science Foundation of China (No.81830065). National Natural Science Foundation of China (No. 82270523). Chongqing Postgraduate Research and Innovation Project (No. GYB22285).