Inflammation is a fundamental response of the body to injury and infection, involving complex cellular and molecular mechanisms. While acute inflammation plays a crucial role in defending against pathogens and repairing tissues, chronic inflammation is closely associated with the occurrence and development of various diseases, including cancer, cardiovascular diseases, neurodegenerative diseases, and autoimmune disorders.
The recent advancements in single-cell sequencing technologies have offered an unprecedented perspective on the cellular and molecular heterogeneity of inflammatory responses. Through high-resolution single-cell RNA sequencing, it is possible to uncover the specific gene expression profiles of different types of immune cells during inflammation, thereby providing an in-depth understanding of their functions. Single-cell sequencing also enables the monitoring of dynamic changes in cellular gene expression at different time points, tracking the key molecular expression patterns during the inflammatory process. Additionally, in combination with spatial transcriptomics techniques, single-cell sequencing can analyze the spatial distribution of cells in tissues and their gene expression, mapping out detailed cellular maps of inflammatory sites and identifying the cellular characteristics and interaction networks in different regions. The latest technological developments also include the integrated analysis of multi-omics data such as single-cell ATAC-seq, DNA sequencing, and proteomics, providing more comprehensive cellular functional information and revealing the complex mechanisms of gene expression regulation. Simultaneously, the application of novel computational tools and algorithms enables researchers to extract meaningful biological information from complex data and uncover the key pathways and molecular mechanisms in inflammatory responses. Therefore, this Research Topic aims to showcase the latest progress of single-cell sequencing technologies in inflammation research.
We invite researchers interested in this topic to submit original research, brief research reports, and review articles, mainly but not limited to the following sub-themes:
1. New applications of single-cell RNA sequencing in the study of inflammatory processes.
2. Single-cell epigenomics and transcriptomics in inflammatory diseases.
3. Identification of key inflammatory mediators, signaling pathways, and immune cell heterogeneity at the single-cell level.
4. Interactions between immune and non-immune cells in the inflammatory microenvironment.
5. Identification of novel therapeutic targets and the development of personalized medical approaches for inflammatory diseases based on single-cell analysis.
6. Single-cell analysis of drug responses and resistance mechanisms in inflammation.
7. Innovations in single-cell sequencing technologies related to inflammation research.
Please note that manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by robust and relevant validation (clinical cohort or biological validation in vitro or in vivo) are out of scope for this Research Topic.
Inflammation is a fundamental response of the body to injury and infection, involving complex cellular and molecular mechanisms. While acute inflammation plays a crucial role in defending against pathogens and repairing tissues, chronic inflammation is closely associated with the occurrence and development of various diseases, including cancer, cardiovascular diseases, neurodegenerative diseases, and autoimmune disorders.
The recent advancements in single-cell sequencing technologies have offered an unprecedented perspective on the cellular and molecular heterogeneity of inflammatory responses. Through high-resolution single-cell RNA sequencing, it is possible to uncover the specific gene expression profiles of different types of immune cells during inflammation, thereby providing an in-depth understanding of their functions. Single-cell sequencing also enables the monitoring of dynamic changes in cellular gene expression at different time points, tracking the key molecular expression patterns during the inflammatory process. Additionally, in combination with spatial transcriptomics techniques, single-cell sequencing can analyze the spatial distribution of cells in tissues and their gene expression, mapping out detailed cellular maps of inflammatory sites and identifying the cellular characteristics and interaction networks in different regions. The latest technological developments also include the integrated analysis of multi-omics data such as single-cell ATAC-seq, DNA sequencing, and proteomics, providing more comprehensive cellular functional information and revealing the complex mechanisms of gene expression regulation. Simultaneously, the application of novel computational tools and algorithms enables researchers to extract meaningful biological information from complex data and uncover the key pathways and molecular mechanisms in inflammatory responses. Therefore, this Research Topic aims to showcase the latest progress of single-cell sequencing technologies in inflammation research.
We invite researchers interested in this topic to submit original research, brief research reports, and review articles, mainly but not limited to the following sub-themes:
1. New applications of single-cell RNA sequencing in the study of inflammatory processes.
2. Single-cell epigenomics and transcriptomics in inflammatory diseases.
3. Identification of key inflammatory mediators, signaling pathways, and immune cell heterogeneity at the single-cell level.
4. Interactions between immune and non-immune cells in the inflammatory microenvironment.
5. Identification of novel therapeutic targets and the development of personalized medical approaches for inflammatory diseases based on single-cell analysis.
6. Single-cell analysis of drug responses and resistance mechanisms in inflammation.
7. Innovations in single-cell sequencing technologies related to inflammation research.
Please note that manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by robust and relevant validation (clinical cohort or biological validation in vitro or in vivo) are out of scope for this Research Topic.