Profiling of microdissected gastric epithelial cells reveals a cell type-specific response to Helicobacter pylori
Anne Mueller1, D Scott Merrell, Jan Grimm
1Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA. muellera@stanford.edu
Background And Aims:
Helicobacter pylori colonizes the epithelial lining of the human stomach and is associated with disorders ranging from chronic gastritis to peptic ulcers and gastric cancer. We have explored the transcriptional response of the epithelium globally by applying a whole-genome approach to a murine model of infection.
Methods:
The 3 major epithelial lineages of the stomach-the parietal, mucus-producing, and chief cells-were harvested from cryosections of infected and uninfected murine stomachs by laser microdissection and subjected to gene expression profiling. The localization and quantity of selected transcripts were verified by in situ hybridization and quantitative real-time reverse-transcription polymerase chain reaction.
Results:
Each cell type is characterized by a transcriptional signature profile. The parietal cell profile is highly enriched for factors involved in mitochondrial energy generation, whereas the chief cell predominantly expresses digestive enzymes and glycosylation-associated proteins. In contrast, the mucus cell signature is distinguished by an abundance of cell-surface receptors, signaling molecules, and factors involved in antigen presentation. All of these indicate a role in sampling, sensing, and responding to environmental stimuli. In line with this biological function, we measured a strong transcriptional response to Helicobacter pylori infection only in this cell type. The genes that are differentially expressed upon infection are implicated in a proinflammatory and mucosal defense response as well as modulation of angiogenesis, iron availability, and tumor suppression.
Conclusions:
Laser microdissection-assisted transcriptional profiling is a useful tool to explore the biology of specific cell populations and is sensitive enough to measure the transcriptional response to bacterial infection in vivo.
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