scImmOmics: A powerful new database for exploring immune cells

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Image credit: Nucleic Acids Research, https://doi.org/10.1093/nar/gkae985

Imagine the immune system as a complex army, with different types of cells working together to protect the body from disease. Scientists are increasingly studying these cells at the single-cell level – examining individual 'soldiers' rather than the whole army – to understand their unique roles. The scImmOmics database has been created to help researchers with this work.

What is scImmOmics?ScImmOmics is a specialised database focused on immune cells, compiled from many different studies. It’s like a vast library of information about immune cells. Currently, the database contains data from over 2.9 million labelled immune cells, making it easier for researchers to study them.

Multi-omics Data: The data in scImmOmics comes from seven different single-cell sequencing technologies:
  • scRNA-seq: Examines the RNA within a cell to determine which genes are active.
  • scTCR-seq & scBCR-seq: Analyses T-cell and B-cell receptors, essential for recognizing threats.
  • scATAC-seq: Maps areas of the genome that are accessible, showing how genes are regulated.
  • CITE-seq & ECCITE-seq: Measures both RNA and protein levels in the same cell.
  • scCUT&Tag-pro: Provides information on DNA and protein states within cells.
By combining data from these different technologies, researchers can obtain a more complete understanding of each cell's behavior.
  • Diverse Cell Types: The database covers 131 immune cell types, 47 tissues, and 4 species, allowing researchers to study immune cells in various contexts.
Why is scImmOmics important?
Understanding the complexities of the immune system is key to developing new treatments for diseases such as cancer and autoimmune disorders. ScImmOmics is valuable because it provides:
  • Standardized data: The database uses consistent naming and organization for immune cells, facilitating comparisons between studies and data sharing. The hierarchical tree structure of the cell types helps to show lineage relationships within the immune system.
  • Comprehensive regulatory information: scImmOmics provides extensive information on how immune cells are regulated. This includes data on gene expression, chromatin accessibility, protein levels, and transcription factors. It also includes information on cell communication, responses to cytokines, and the clonotypes of T and B cells.
  • User-friendly interface: The database has a website with search, browse, analysis, and download functions. Tools are available for comparing datasets, performing gene enrichment analysis, and assessing immune responses to cytokines.
  • Manual curation: Unlike some other databases, the information in scImmOmics has been reviewed and annotated by experts, ensuring accuracy and reliability.
How was scImmOmics constructed?
The development of the database involved an extensive search of scientific publications focusing on single-cell sequencing of immune cells. The team downloaded the data, extracted the immune cells, and then standardized the information to ensure consistency.
Key features of the scImmOmics database include:
  • Search functionality: Users can search for data by tissue type, disease, or cell type, with the search results providing a summary of the dataset and the corresponding publication.
  • Visualisations: The database uses visualisations such as UMAP projections, heatmaps and charts to make it easier to understand the data.
  • Analytical tools: Tools for identifying differentially expressed genes, performing gene enrichment analysis, and comparing datasets are provided.
  • Downloadable data: The raw data and metadata are available for download for further analysis.
Case studies
The source provides examples of how scImmOmics can be used in research. In one study, analysis of peripheral blood mononuclear cell (PBMC) data confirmed that B cells showed higher expression of the markers CD19 and CD22. The database was also used to analyse bone marrow data, which showed the correct expression of markers and TFs in the relevant cell types. These examples demonstrate how the database facilitates multi-omics views of immune cell biology.

  • For example, when analysing PBMC data, the database showed higher expression of CD19 and CD22 in B cells, which is consistent with known biology. It further identified these markers as B cell-specific differentially expressed genes.
  • Function enrichment analysis confirmed the association of these DEGs with B cells as they were enriched in B-cell related pathways.
  • Similarly, when analysing bone marrow data, the database highlighted high expression of markers CD86, CD33 and CD69 and the transcription factor IRF4 in the corresponding cell types.
Future developments
The developers of scImmOmics plan to expand the database by adding more data, including new types of sequencing data such as spatial transcriptomics and more information about diseases. They also plan to further improve the analysis tools and the user interface. The database is freely available online.

In conclusion
ScImmOmics is a powerful new resource for researchers studying the immune system. By bringing together a large amount of single-cell data and providing analysis tools, it offers the potential to deepen understanding of immune function and lead to the development of new treatments for a range of diseases. The database provides a comprehensive and user-friendly platform to facilitate new scientific discoveries.
 
Additional information: scImmOmics: a manually curated resource of single-cell multi-omics immune data. Nucleic Acids Research, https://doi.org/10.1093/nar/gkae985

Journal information: https://academic.oup.com/

Location: Oxford, UK

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