Single-cell entropy network detects the activity of immune cells based on ribosomal protein genes

Jin, Qiqi; Zuo, Chunman; Cui, Haoyue; Li, Lin; Yang, Yiwen; Dai, Hao; Chen, Luonan

doi:10.1016/j.csbj.2022.06.056

Cited by 3 publications

(1 citation statement)

References 58 publications

(70 reference statements)

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“…Single-cell RNA sequencing (scRNA-seq), which provides an unbiased approach for characterizing cell diversity and heterogeneous phenotypes at high resolution 7 , 8 , has been used in patients with neurodegenerative disorders or neuroinflammatory conditions, such as Alzheimer’s disease (AD) 9 , multiple sclerosis (MS) 10 , and Parkinson’s disease (PD) 11 . Since the loss of myenteric neurons and ganglionitis was the main pathophysiology in achalasia, we use scRNA-seq to map the immune cell transcriptional landscape of peripheral blood and paired LES tissues from patients with achalasia and controls.…”

Section: Introductionmentioning

confidence: 99%

A single-cell transcriptional landscape of immune cells shows disease-specific changes of T cell and macrophage populations in human achalasia

et al. 2023

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Achalasia is a rare motility disorder of the esophagus caused by the gradual degeneration of myenteric neurons. Immune-mediated ganglionitis has been proposed to underlie the loss of myenteric neurons. Here, we measure the immune cell transcriptional profile of paired lower esophageal sphincter (LES) tissue and blood samples in achalasia and controls using single-cell RNA sequencing (scRNA-seq). In achalasia, we identify a pattern of expanded immune cells and a specific transcriptional phenotype, especially in LES tissue. We show C1QC+ macrophages and tissue-resident memory T cells (TRM), especially ZNF683+ CD8+ TRM and XCL1+ CD4+ TRM, are significantly expanded and localized surrounding the myenteric plexus in the LES tissue of achalasia. C1QC+ macrophages are transcriptionally similar to microglia of the central nervous system and have a neurodegenerative dysfunctional phenotype in achalasia. TRM also expresses transcripts of dysregulated immune responses in achalasia. Moreover, inflammation increases with disease progression since immune cells are more activated in type I compared with type II achalasia. Thus, we profile the immune cell transcriptional landscape and identify C1QC+ macrophages and TRM as disease-associated immune cell subsets in achalasia.

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Section: Introductionmentioning

confidence: 99%

A single-cell transcriptional landscape of immune cells shows disease-specific changes of T cell and macrophage populations in human achalasia

et al. 2023

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Early life adversity is associated with differential gene expression in immune cells: A cluster-based analysis across an acute psychosocial stressor

Etzel,

Apsley,

Hastings

et al. 2024

Brain, Behavior, and Immunity

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SGAE: single-cell gene association entropy for revealing critical states of cell transitions during embryonic development

Zhong,

Han,

Chen

et al. 2023

Briefings in Bioinformatics

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The critical point or pivotal threshold of cell transition occurs in early embryonic development when cell differentiation culminates in its transition to specific cell fates, at which the cell population undergoes an abrupt and qualitative shift. Revealing such critical points of cell transitions can track cellular heterogeneity and shed light on the molecular mechanisms of cell differentiation. However, precise detection of critical state transitions proves challenging when relying on single-cell RNA sequencing data due to their inherent sparsity, noise, and heterogeneity. In this study, diverging from conventional methods like differential gene analysis or static techniques that emphasize classification of cell types, an innovative computational approach, single-cell gene association entropy (SGAE), is designed for the analysis of single-cell RNA-seq data and utilizes gene association information to reveal critical states of cell transitions. More specifically, through the translation of gene expression data into local SGAE scores, the proposed SGAE can serve as an index to quantitatively assess the resilience and critical properties of genetic regulatory networks, consequently detecting the signal of cell transitions. Analyses of five single-cell datasets for embryonic development demonstrate that the SGAE method achieves better performance in facilitating the characterization of a critical phase transition compared with other existing methods. Moreover, the SGAE value can effectively discriminate cellular heterogeneity over time and performs well in the temporal clustering of cells. Besides, biological functional analysis also indicates the effectiveness of the proposed approach.

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Single-cell entropy network detects the activity of immune cells based on ribosomal protein genes

Cited by 3 publications

References 58 publications

A single-cell transcriptional landscape of immune cells shows disease-specific changes of T cell and macrophage populations in human achalasia

A single-cell transcriptional landscape of immune cells shows disease-specific changes of T cell and macrophage populations in human achalasia

Early life adversity is associated with differential gene expression in immune cells: A cluster-based analysis across an acute psychosocial stressor

SGAE: single-cell gene association entropy for revealing critical states of cell transitions during embryonic development

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