Single-cell RNA sequencing reveals cell–cell communication and potential biomarker in sepsis and septic shock patients

Li, Guilin; Yang, Zhaoxu; Yang, Chen; Xie, Yaochen; Gong, Shuchen; Lv, Shuying; Xiao, Boneng; Wang, Jiajia; Weng, Qinjie; Wang, Jincheng; Yu, Feng

doi:10.1016/j.intimp.2024.111938

Cited by 1 publication

(1 citation statement)

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“…It has been shown that myeloid cells are increased in number but lacking in function in sepsis (6). Guilin Li et al reveals that the molecules CAP-1 and IL16 on monocytes may serve as potential diagnostic markers for sepsis based on sc-RNA analysis (7). Single-cell RNA sequencing (scRNA-seq) analysis revealed a new role of circulating MAIT17 in promoting sepsis severity and suggests the PI3K-LDHA signaling as a driving force in MAIT17 responses (8).…”

Section: Introductionmentioning

confidence: 99%

Integrated multi-omics and artificial intelligence to explore new neutrophils clusters and potential biomarkers in sepsis with experimental validation

Xu,

Tao,

Zhang

2024

Front. Immunol.

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BackgroundSepsis, causing serious organ and tissue damage and even death, has not been fully elucidated. Therefore, understanding the key mechanisms underlying sepsis-associated immune responses would lead to more potential therapeutic strategies.MethodsSingle-cell RNA data of 4 sepsis patients and 2 healthy controls in the GSE167363 data set were studied. The pseudotemporal trajectory analyzed neutrophil clusters under sepsis. Using the hdWGCNA method, key gene modules of neutrophils were explored. Multiple machine learning methods were used to screen and validate hub genes for neutrophils. SCENIC was then used to explore transcription factors regulating hub genes. Finally, quantitative reverse transcription-polymerase chain reaction was to validate mRNA expression of hub genes in peripheral blood neutrophils of two mice sepsis models.ResultsWe discovered two novel neutrophil subtypes with a significant increase under sepsis. These two neutrophil subtypes were enriched in the late state during neutrophils differentiation. The hdWGCNA analysis of neutrophils unveiled that 3 distinct modules (Turquoise, brown, and blue modules) were closely correlated with two neutrophil subtypes. 8 machine learning methods revealed 8 hub genes with high accuracy and robustness (ALPL, ACTB, CD177, GAPDH, SLC25A37, S100A8, S100A9, and STXBP2). The SCENIC analysis revealed that APLP, CD177, GAPDH, S100A9, and STXBP2 were significant associated with various transcriptional factors. Finally, ALPL, CD177, S100A8, S100A9, and STXBP2 significantly up regulated in peripheral blood neutrophils of CLP and LPS-induced sepsis mice models.ConclusionsOur research discovered new clusters of neutrophils in sepsis. These five hub genes provide novel biomarkers targeting neutrophils for the treatment of sepsis.

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Section: Introductionmentioning

confidence: 99%