Integrating single-cell sequencing and transcriptome analysis to unravel the mechanistic role of sialylation-related genes in sepsis-induced acute respiratory distress syndrome
BackgroundStudies have shown that sialylation of C1 esterase inhibitors is crucial for their interaction with histones, and histone-C1 esterase inhibitor complexes are detected in acute respiratory distress syndrome (ARDS), suggesting a potential role of sialylation in ARDS. However, the specific fu...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-05-01
|
| Series: | Frontiers in Immunology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1528769/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849713173555314688 |
|---|---|
| author | Xiaobing Liu Yake Huang Hao Zhang Xia Yang Quanxing Liu Jigang Dai |
| author_facet | Xiaobing Liu Yake Huang Hao Zhang Xia Yang Quanxing Liu Jigang Dai |
| author_sort | Xiaobing Liu |
| collection | DOAJ |
| description | BackgroundStudies have shown that sialylation of C1 esterase inhibitors is crucial for their interaction with histones, and histone-C1 esterase inhibitor complexes are detected in acute respiratory distress syndrome (ARDS), suggesting a potential role of sialylation in ARDS. However, the specific function of sialylation in ARDS remains unclear. Therefore, this study aimed to investigate the mechanism of sialylation-related genes (SRGs) in sepsis-induced ARDS.MethodsThe ARDS related datasets (GSE32707, GSE66890, and GSE151263) were included in this study. Candidate genes were identified by implementing differential expression analysis and weighted gene co-expression network analysis (WGCNA). Subsequently, further selection by machine learning and expression assessment confirmed the key genes related to sialylation in sepsis-induced ARDS. Following this, the predictive ability of key genes as a whole for sepsis-induced ARDS was evaluated by creating a nomogram model. Afterwards, enrichment analysis, construction of regulatory networks, and drug prediction analysis were implemented to further understand the molecular mechanisms of action of key genes. Furthermore, single-cell RNA sequencing (scRNA-seq) data analysis was conducted to obtain key cells. Additionally, cell communication and pseudo-time analyses were implemented. In the end, the expression levels of the key genes were assessed by collecting clinical samples.ResultsCD19 and GPR65 were identified as key genes associated with sialylation in sepsis-induced ARDS. The constructed nomogram model demonstrated that CD19 and GPR65 as a whole exhibited robust predictive capability for sepsis-induced ARDS. Meanwhile, CD19 and GPR65 were also found to be significantly co-enriched in the apoptosis and B-cell receptor signaling pathway. In addition, some important regulators and drugs with targeting effects on key genes were predicted, such as NEAT1, OIP5-AS1, alprostadil, and tacrolimus. Further, the scRNA-seq data analysis identified nine cell types, among which CD14 monocytes (CD14Mono) was designated as the key cell. Importantly, GPR65 expression exhibited dynamic changes during differentiation of CD14Mono. Also, we found that CD19 was significantly up-regulated in ARDS group.ConclusionWe identified CD19 and GPR65 as key genes associated with sialylation in sepsis-induced ARDS, highlighting CD14Mono as key cell type implicated in sepsis-induced ARDS. These findings offered theoretical support for understanding the mechanism of sialylation on sepsis-induced ARDS. |
| format | Article |
| id | doaj-art-c3fc50e0026c4eae9f6be2808cf2f28c |
| institution | DOAJ |
| issn | 1664-3224 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj-art-c3fc50e0026c4eae9f6be2808cf2f28c2025-08-20T03:14:01ZengFrontiers Media S.A.Frontiers in Immunology1664-32242025-05-011610.3389/fimmu.2025.15287691528769Integrating single-cell sequencing and transcriptome analysis to unravel the mechanistic role of sialylation-related genes in sepsis-induced acute respiratory distress syndromeXiaobing Liu0Yake Huang1Hao Zhang2Xia Yang3Quanxing Liu4Jigang Dai5Department of Thoracic Surgery, Xinqiao Hospital, Army Medical University (Third Military Medical University), Chongqing, ChinaDepartment of Obstetrics and Gynecology, Xinqiao Hospital, Army Medical University (Third Military Medical University), Chongqing, ChinaDepartment of Critical Care Medicine, Daping Hospital, Army Medical University (Third Military Medical University), Chongqing, ChinaDepartment of Wound Infection and Drug, State Key Laboratory of Trauma and Chemical Poisoning, Daping Hospital, Army Medical University (Third Military Medical University), Chongqing, ChinaDepartment of Thoracic Surgery, Xinqiao Hospital, Army Medical University (Third Military Medical University), Chongqing, ChinaDepartment of Thoracic Surgery, Xinqiao Hospital, Army Medical University (Third Military Medical University), Chongqing, ChinaBackgroundStudies have shown that sialylation of C1 esterase inhibitors is crucial for their interaction with histones, and histone-C1 esterase inhibitor complexes are detected in acute respiratory distress syndrome (ARDS), suggesting a potential role of sialylation in ARDS. However, the specific function of sialylation in ARDS remains unclear. Therefore, this study aimed to investigate the mechanism of sialylation-related genes (SRGs) in sepsis-induced ARDS.MethodsThe ARDS related datasets (GSE32707, GSE66890, and GSE151263) were included in this study. Candidate genes were identified by implementing differential expression analysis and weighted gene co-expression network analysis (WGCNA). Subsequently, further selection by machine learning and expression assessment confirmed the key genes related to sialylation in sepsis-induced ARDS. Following this, the predictive ability of key genes as a whole for sepsis-induced ARDS was evaluated by creating a nomogram model. Afterwards, enrichment analysis, construction of regulatory networks, and drug prediction analysis were implemented to further understand the molecular mechanisms of action of key genes. Furthermore, single-cell RNA sequencing (scRNA-seq) data analysis was conducted to obtain key cells. Additionally, cell communication and pseudo-time analyses were implemented. In the end, the expression levels of the key genes were assessed by collecting clinical samples.ResultsCD19 and GPR65 were identified as key genes associated with sialylation in sepsis-induced ARDS. The constructed nomogram model demonstrated that CD19 and GPR65 as a whole exhibited robust predictive capability for sepsis-induced ARDS. Meanwhile, CD19 and GPR65 were also found to be significantly co-enriched in the apoptosis and B-cell receptor signaling pathway. In addition, some important regulators and drugs with targeting effects on key genes were predicted, such as NEAT1, OIP5-AS1, alprostadil, and tacrolimus. Further, the scRNA-seq data analysis identified nine cell types, among which CD14 monocytes (CD14Mono) was designated as the key cell. Importantly, GPR65 expression exhibited dynamic changes during differentiation of CD14Mono. Also, we found that CD19 was significantly up-regulated in ARDS group.ConclusionWe identified CD19 and GPR65 as key genes associated with sialylation in sepsis-induced ARDS, highlighting CD14Mono as key cell type implicated in sepsis-induced ARDS. These findings offered theoretical support for understanding the mechanism of sialylation on sepsis-induced ARDS.https://www.frontiersin.org/articles/10.3389/fimmu.2025.1528769/fullsepsis-induced acute respiratory distress syndromesialylationnomogramsingle-cell RNA sequencingkey genes |
| spellingShingle | Xiaobing Liu Yake Huang Hao Zhang Xia Yang Quanxing Liu Jigang Dai Integrating single-cell sequencing and transcriptome analysis to unravel the mechanistic role of sialylation-related genes in sepsis-induced acute respiratory distress syndrome Frontiers in Immunology sepsis-induced acute respiratory distress syndrome sialylation nomogram single-cell RNA sequencing key genes |
| title | Integrating single-cell sequencing and transcriptome analysis to unravel the mechanistic role of sialylation-related genes in sepsis-induced acute respiratory distress syndrome |
| title_full | Integrating single-cell sequencing and transcriptome analysis to unravel the mechanistic role of sialylation-related genes in sepsis-induced acute respiratory distress syndrome |
| title_fullStr | Integrating single-cell sequencing and transcriptome analysis to unravel the mechanistic role of sialylation-related genes in sepsis-induced acute respiratory distress syndrome |
| title_full_unstemmed | Integrating single-cell sequencing and transcriptome analysis to unravel the mechanistic role of sialylation-related genes in sepsis-induced acute respiratory distress syndrome |
| title_short | Integrating single-cell sequencing and transcriptome analysis to unravel the mechanistic role of sialylation-related genes in sepsis-induced acute respiratory distress syndrome |
| title_sort | integrating single cell sequencing and transcriptome analysis to unravel the mechanistic role of sialylation related genes in sepsis induced acute respiratory distress syndrome |
| topic | sepsis-induced acute respiratory distress syndrome sialylation nomogram single-cell RNA sequencing key genes |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1528769/full |
| work_keys_str_mv | AT xiaobingliu integratingsinglecellsequencingandtranscriptomeanalysistounravelthemechanisticroleofsialylationrelatedgenesinsepsisinducedacuterespiratorydistresssyndrome AT yakehuang integratingsinglecellsequencingandtranscriptomeanalysistounravelthemechanisticroleofsialylationrelatedgenesinsepsisinducedacuterespiratorydistresssyndrome AT haozhang integratingsinglecellsequencingandtranscriptomeanalysistounravelthemechanisticroleofsialylationrelatedgenesinsepsisinducedacuterespiratorydistresssyndrome AT xiayang integratingsinglecellsequencingandtranscriptomeanalysistounravelthemechanisticroleofsialylationrelatedgenesinsepsisinducedacuterespiratorydistresssyndrome AT quanxingliu integratingsinglecellsequencingandtranscriptomeanalysistounravelthemechanisticroleofsialylationrelatedgenesinsepsisinducedacuterespiratorydistresssyndrome AT jigangdai integratingsinglecellsequencingandtranscriptomeanalysistounravelthemechanisticroleofsialylationrelatedgenesinsepsisinducedacuterespiratorydistresssyndrome |