RNA-seq-based screening of autophagy-related genes during lung infection by highly antibiotic-resistant and highly virulent Staphylococcus aureus
10.19405/j.cnki.issn1000-1492.2025.09.016
- VernacularTitle:基于 RNA-seq 筛选高耐药且高毒力金黄色葡萄球菌 肺部感染过程中的自噬相关基因
- Author:
Jinhong Zha
1
;
Qi Kuang
1
;
Chengxi Wu
2
;
Xiaoyu Zhu
2
;
Duo Su
2
;
Lili Zhang
2
;
Meng Lyu
2
;
Lingfei Hu
2
;
Dongsheng Zhou
2
;
Wenhui Yang
1
Author Information
1. School of Basic Medical Sciences，Anhui Medical University，Hefei 230032;Academy of Military Medical Sciences，Academy of Military Sciences，Beijing 100071
2. Academy of Military Medical Sciences，Academy of Military Sciences，Beijing 100071
- Publication Type:Journal Article
- Keywords:
methicillin-resistant Staphylococcus aureus;
mouse;
pneumonia;
autophagy;
key genes;
immune infiltration;
bioinformatics
- From:
Acta Universitatis Medicinalis Anhui
2025;60(9):1689-1696
- CountryChina
- Language:Chinese
-
Abstract:
Objective :To identify autophagy-related genes involved in pulmonary infection caused by the highly drug-resistant and virulent methicillin-resistant Staphylococcus aureus strain USA300 ( USA300) ，and to explore the underlying molecular mechanisms ， thereby providing potential targets for immunotherapy．
Methods:The GSE220943 dataset of a USA300-induced pulmonary infection mouse model was obtained from the GEO database． Differentially expressed genes ( DEGs ) were identified using the DESeq2 package． Autophagy-related genes ( ARGs) were retrieved from the MSigDB and Autophagy databases．Weighted gene co-expression network analysis ( WGCNA) was performed to construct gene co-expression modules．Genes overlapping among DEGs，ARGs，and WGCNA modules were identified as autophagy-related DEGs．Gene Ontology ( GO) enrichment analysis was con- ducted using the clusterProfiler R package，while Kyoto Encyclopedia of Genes and Genomes ( KEGG) pathway en- richment analysis was performed via the Metascape platform．Immune cell infiltration was analyzed using the Immu- CellAI-mouse website．A protein - protein interaction ( PPI) network was constructed using the STRING database， and hub genes were identified through topological analysis in Cytoscape． Receiver operating characteristic curve ( ROC) curves were plotted via the website https: / /www．bioinformatics．com．cn． Finally，key gene expression was validated in mouse lung tissues by real-time quantitative reverse transcription PCR ( RT-qPCR) ．
Results:A total of 6 135，4 075，3 680，and 2 342 differentially expressed genes ( DEGs) were identified at 12，24，48，and 96 hours post-infection，respectively．By integrating DEGs，autophagy-related genes ( ARGs) ，and WGCNA mod- ules，19 autophagy-related DEGs were identified． GO and KEGG enrichment analyses indicated that these genes were mainly involved in CD4 + T cell activation and regulation，innate immune responses，and autophagosome mem- brane formation．Immune infiltration analysis revealed that innate immune cells such as neutrophils and dendritic cells predominated during the early phase of infection，while γδ T cells and M2 macrophages became more promi- nent in the later stages．PPI network analysis identified 12 hub autophagy-related genes，among which three upreg- ulated key genes ( Eif2ak2，Ikbke，and Nfkbiz) were further confirmed．The area under the ROC curve for all three genes was 1. 000．RT-qPCR validation demonstrated significantly elevated expression of these three genes in lung tissues at 24 hours post-infection ( all P＜0. 05) ．
Conclusion:Eif2ak2，Ikbke，and Nfkbiz may be involved in the pulmonary infection caused by USA300 by promoting autophagy and hold promise as potential targets for immuno- therapy．
- Full text:202603281311280529基于RNA-seq筛选高耐药且高毒力金黄色葡萄球菌肺部感染过程中的自噬相关基因_查锦宏.pdf
