Characterization of gene expression profiles for different types of mast cells pooled from mouse stomach subregions by an RNA amplification method
Open accessAbstract
Background: Mast cells (MCs) play pivotal roles in allergy and innate immunity and consist of heterogenous subclasses. However, the molecular basis determining the different characteristics of these multiple MC subclasses remains unclear. Results: To approach this, we developed a method of RNA extraction/amplification for intact in vivo MCs pooled from frozen tissue sections, which enabled us to obtain the global gene expression pattern of pooled MCs belonging to the same subclass. MCs were isolated from the submucosa (sMCs) and mucosa (mMCs) of mouse stomach sections, respectively, 15 cells were pooled, and their RNA was extracted, amplified and subjected to microarray analysis. Known marker genes specific for mMCs and sMCs showed expected expression trends, indicating accuracy of the analysis. We identified 1,272 genes showing significantly different expression levels between sMCs and mMCs, and classified them into clusters on the basis of similarity of their expression profiles compared with bone marrow-derived MCs, which are the cultured MCs with so-called 'immature' properties. Among them, we found that several key genes such as Notch4 had sMC-biased expression and Ptgr1 had mMC-biased expression. Furthermore, there is a difference in the expression of several genes including extracellular matrix protein components, adhesion molecules, and cytoskeletal proteins between the two MC subclasses, which may reflect functional adaptation of each MC to the mucosal or submucosal environment in the stomach. Conclusion: By using the method of RNA amplification from pooled intact MCs, we characterized the distinct gene expression profiles of sMCs and mMCs in the mouse stomach. Our findings offer insight into possible unidentified properties specific for each MC subclass.
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Chromogranin A is a known product of the mast cell.
“CgA is a known product of the MC [59,60]”
From Diagnosis of mast cell activation syndrome: a global "consensus-2" (2021) · cites this paper as [59]
The Background and Results and discussion passages describe mast-cell granule contents and products such as serine proteases and Ptgr1, but do not identify chromogranin A as a mast-cell product. Searches for “chromogranin A” and “CgA mast cell” found no passage addressing that point in our copy; page numbers were not provided. (LLM, conf=0.73)
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- Authors
- Tsuchiya, S., Tachida, Y., Segi-Nishida, E., Okuno, Y., Tamba, S., Tsujimoto, G., Tanaka, S., & Sugimoto, Y.
- Affiliations
- Kyoto University (JP)
- Mukogawa Women's University (JP)
- Corresponding author
- Sugimoto, Yukihiko
- Venue
- BMC Genomics
- Published
- 2009-01-20
- Volume
- 10
- Issue
- 1
- Pages
- 35-35
- ISSN
- 1471-2164 (ISSN-L)
- PMC
- PMC2639374
- OpenAlex
- W2049425443
- Cited by
- 15
- References
- 42
- Citations by year
- 2024: 1 · 2020: 3 · 2019: 1 · 2018: 1 · 2015: 1 · 2013: 1
- FWCI
- 1.01
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- BMC Genomics (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Japan Society for the Promotion of Science
- Topics
- Life Sciences › Immunology and Microbiology › Immunology › Mast cells and histamine
- Health Sciences › Medicine › Physiology › Asthma and respiratory diseases
- Health Sciences › Medicine › Gastroenterology › Gastrointestinal motility and disorders
- Keywords
- mast cells, gene expression profiling, stomach, mucosal mast cells, RNA amplification, Notch4, PTGR1, extracellular matrix proteins, adhesion molecules, cytoskeletal proteins, bone marrow-derived mast cells, mice
- MeSH terms
- Animals, Gastric Mucosa, Mast Cells, RNA, Reproducibility of Results, Cluster Analysis, Reverse Transcriptase Polymerase Chain Reaction, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, Mice
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