Characterization of gene expression profiles for different types of mast cells pooled from mouse stomach subregions by an RNA amplification method
© Tsuchiya et al; licensee BioMed Central Ltd. 2009
Received: 09 July 2008
Accepted: 20 January 2009
Published: 20 January 2009
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.
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.
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.
Mast cells (MCs) are derived from hematopoietic stem cells and play important roles in allergic responses, innate immunity and defense against parasite infection. Unlike other blood cells, MCs migrate into peripheral tissues as immature progenitors and differentiate into mature mast cells. One of the unique features of MCs is that they show a variety of phenotypes depending on the different tissue microenvironment of their maturation . In MCs, various MC-specific serine proteases are stored in the secretory granules, and their gene and protein expressions are dramatically altered when their cell environment is altered. For example, Reynolds et al. have shown that at least six distinct members of mouse MC-specific serine proteases are expressed in different combinations in different mast cell populations . In addition, recent studies have shown that mature MCs vary in terms of what surface receptors and lipid mediators they express [3, 4]. Because each mast cell population in vivo must play a specific role in the body, it is important to determine the character of each population of MCs.
Comprehensive gene expression analysis is a powerful approach to understand the characterization of various MC subpopulations. To date, several studies on microarray analysis of MCs have been conducted [5–7], but most of them dealt with MCs cultured in vitro. Alternatively, gene expression profiles of MCs isolated from skin and lung have been analyzed [3, 8–10]. However, the numbers of MCs analyzed as one sample were relatively high and they were exposed to physical forces, enzymes and the anti-Kit antibody for purification, during which the original properties of the MCs may have been affected.
In the gastrointestinal tract, there are MCs that are mainly classified into two subclasses; mucosal MCs (mMCs) and submucosal MCs (sMCs) on the basis of their location, morphology (size and shape) and granule contents [11, 12]. mMCs are mainly found in the mucosa of the gastrointestinal system, having chondroitin sulfate-containing granules, which are stained with toluidine blue but not safranin, and their activation occurs during parasite infection , while sMCs are localized in the submucosa of the gastrointestinal tract and their granules are rich in heparin and stained with both toluidine blue and safranin [1, 11]. However, the molecular basis determining the differences in biochemical properties of these two MC subclasses remains uncertain, partially due to the difficulty of their isolation.
To overcome these problems, here we established a method of RNA amplification from intact MCs isolated from frozen tissue sections, which enables us to conveniently obtain the global gene expression pattern of MCs in various tissues. To validate this method, we first determined the minimum cell number required to achieve reproducible RNA amplification. We then compared the gene expression profiles obtained from small numbers of mMCs and sMCs in the mouse stomach, and found several key genes to be specifically expressed in one subclass of MCs, which may reflect some aspects of the distinct properties between the two MC subclasses in the gastrointestinal tract.
Results and discussion
Development of an RNA amplification protocol to obtain gene expression profiles from a small amount of RNA
Gene expression profiles of submucosal and mucosal MCs from the stomach
To visualize two kinds of MCs in the stomach without causing RNA degradation, the sections were fixed with carnoy's fixative and metachromatically stained with toluidine blue for a few seconds. sMCs and mMCs were microdissected using a patch pipette (Figure 2a and 2b). We prepared three sets of 15 MCs for each region, extracted their RNA and individually amplified them (sMC1, sMC2, sMC3, and mMC1, mMC2, mMC3). To improve the recovery of the extraction of as little as 30 pg of RNA, we used 'poly G' as a carrier, which does not interfere with the following RNA amplification or hybridization of the amplified product to the array (data not shown). To examine the effects of nonspecifically amplified artifact products, we performed the RNA extraction/amplification procedure without adding microdissected cells ("no cell") as a negative control (described in "Materials and methods"). The amplified RNAs of sMCs, mMCs and the "no cell" control were separately hybridized to a murine microarray. The signal values in the "no cell" sample were low in general and similar to the background levels (Figure 2c). The scatter plots of the samples independently prepared within the same group (e.g. sMC1 vs sMC2) showed a similar expression pattern; the average correlation coefficient for all probe-sets was 0.945 ± 0.004 and 0.893 ± 0.019 in sMCs and mMCs, respectively (n = 3). In contrast, the average correlation coefficient between sMCs and mMCs was 0.752 ± 0.034 (n = 3), which was much lower than those within the same group, suggesting that their gene expression patterns are different.
We then compared the stomach-derived MCs (sMCs and mMCs) with skin-derived MCs, peritoneal MCs, BMMCs and non-MCs (macrophages and fibroblasts) by clustering analysis. The tissue-derived MCs (stomach MCs and skin MCs) were clustered separately from peritoneal MCs and BMMCs. These results may reflect different properties between tissue-derived MCs with firm adhesion to the neighboring cells and floating MCs without a tight contact. As to the similarity of MCs with fibroblasts and macrophages, it is reasonable that fibroblasts are most distant from MCs and macrophages are closer to MCs as a leukocyte family.
Validation of microarray results by real time RT-PCR analysis
Summary of genes examined by real-time PCR analysis.
RefSeq Transcript ID
Fc fragment of IgE, high affinity I, receptor for α polypeptide
mast cell protease 1
mast cell protease 2
mast cell protease 4
chymase 2, mast cell (mast cell protease 10)
FBJ osteosarcoma oncogene
Prostaglandin reductase 1 (leukotriene B4 12-hydroxydehydrogenase)
Notch gene homolog 4
28S ribosomal RNA
Clustering analysis of the gene expression profiles and functional categorization between sMCs and mMCs
Protein expression of Notch4 in sMCs and Ptgr1 in mMCs in stomach tissue
The Ptgr1 product, 15-oxo-prostaglandin 13-reductase/leukotriene (LT) B4 12-hydroxydehydrogenase is an essential enzyme for inactivation of eicosanoids such as prostaglandin E2 (PGE2) and LTB4 . Although it has been reported that the pathways of eicosanoid synthesis differ among the different MC subclasses [1, 4], our results suggest that the inactivation system of eicosanoids also varies among the MC subclasses. Ptgr1 expression was found to be significantly higher in the separately pooled mMCs by real-time RT-PCR (data not shown). We also examined Ptgr1 expression in stomach sections by immunostaining. Signals for the Ptgr1 protein were found in granule-like structures of mMCs in the stomach mucosa but not in sMCs (Figure 6b), suggesting that the Ptgr1 enzyme may be released from mMCs upon degranulation. Since PGE2 plays critical roles in the maintenance of gut homeostasis through mucosal protection and inhibition of acid secretion, it is possible that when activated, mMCs negatively regulate the cytoprotective actions of PGE2 through rapid inactivation by Ptgr1.
Gene expression pattern of extracellular matrix components, adhesion molecules, and cytoskeletal proteins in sMCs and mMCs
MC phenotypes have been shown to depend on their interactions with the surrounding extracellular matrices (ECMs) and neighboring cells . One of the most remarkable findings in this study is the difference in gene expression of ECM protein components, adhesion molecules, and cytoskeletal proteins, which may reflect functional adaptation of each type of MC to the mucosal or submucosal environment in the stomach (Figure 5b). mMCs express genes for mucosa-specific ECM proteins such as Muc1 (Mucin) and Tff1 (Trefoil factor), while sMCs express genes for conventional ECM proteins such as Col4a (procollagen) and Lama2 (laminin). Moreover, sMCs express genes for adhesion molecules such as Alcam and Vcam1, and genes for ordinary cytoskeletal proteins such as Acta2 (actin), while mMCs express desmosome-component genes such as Dsc2 (desmocollin) and Dsg2 (desmoglein), and genes for keratin intermediate filaments such as Krt8 and Krt19. Desmosomes were reported to be present in the stomach epithelia , and it was found that desmosome-like structures are detected in a particular type of MC . It is thus possible that mMCs interact with adjacent epithelia through desmosomal adhesion in the stomach. In contrast, sMCs appear to interact with neighboring cells via adhesion molecules such as VCAM-1, ALCAM and VE-cadherin (Vcam1, Alcam1 and Cdh5). Since these adhesion molecules have been shown to be involved in dynamic regulation of the actin cytoskeleton [37, 38], such molecule-mediated interactions with submucosal cells may be critical to maintain the functional and morphological properties of sMCs. Indeed, it should be noted that most sMCs are variable in shape, and are often stretched and winding as compared with mMCs .
We established a method of RNA amplification from pooled intact MCs isolated from frozen tissue sections, which enables us to conveniently obtain the global gene expression pattern of MCs from various tissues, organs, and species including humans. By using this method, we demonstrated for the first time the distinct gene expression profiles of submucosal and mucosal MCs in the mouse stomach. Our findings offer insight into possible unidentified properties specific for each MC subclass.
The following materials were obtained from the sources indicated: HPLC purified T7-(dT)24 primer [5'-GGCCAGTGAATTGTAATACGACTCACTATAGGGAGGC GG(T)24] from GE Healthcare UK Ltd. (Buckinghamshire, England), RNase-free water, dNTP, SusperScript II, Escherichia coli (E. coli) RNase H, E. coli DNA polymerase I, E. coli DNA ligase, T4 DNA polymerase and random hexamers from Invitrogen (San Diego, CA), RNase inhibitor, glycogen, and MEGAscript T7 kit from Ambion (Austin, TX). Balb/c mice were obtained from JapanClea (Hamamatsu, Japan). This study was approved by the Committee on Animal Research of Kyoto University Graduate School of Pharmaceutical Sciences.
RNA amplification and oligonucleotide microarray
Mouse interleukin-3-dependent BMMCs were prepared as described previously . Total RNA of BMMCs was extracted using RNeasy mini kit (Qiagen, Valencia, CA). Five micrograms of total RNA from BMMCs were labeled and prepared for hybridization according to the manufacturer's instructions (standard protocol). On the other hand, 30 pg, 10 pg and 2 pg of BMMC total RNA were amplified and labeled by our original three-round amplification method, which is described below.
Total RNA was incubated with T7-(dT)24 primer and first-strand cDNA was then synthesized by SuperScript II (Invitrogen). Second-strand synthesis was carried out by adding RNase H, DNA polymerase I and DNA ligase. The antisense RNA was synthesized using MEGAscript T7 kit.
The antisense RNA product was annealed with random hexamers, and cDNA was again synthesized by SuperScript II. Then, the RNA-cDNA hybrid was digested with RNase H and annealed with the T7-(dT)24 primer, and then second-strand synthesis was carried out by adding DNA polymerase I. The antisense RNA was again synthesized using MEGAscript T7 kit. Quality and size distribution of the antisense RNA product were confirmed by an RNA 6000 Nano LabChip on the Agilent Bioanalyzer (Palo Alto, CA).
As in the case of the second round, the double-stranded cDNA with a T7-promoter sequence was prepared from the second-round RNA product. Biotin-labeled antisense RNA was synthesized by RNA Transcript Labeling Kit (Enzo, Farmingdale, NY).
These labeled RNAs were hybridized to GeneChip Murine Expression oligonucleotide arrays (Affymetrix, Santa Clara, CA). We used microarray suite 5.0 of Affymetrix GeneChip Operating Software for quantification of the GeneChip data and decision of "Presence" or "Absence" of expression of each probe set using the values of 11 paired (perfect-matched and mismatched) probes.
Microdissection of MCs from tissue sections, RNA extraction, and microarray data analysis
Tissue sections 7 μm in thickness were prepared using a Jung Frigocut 3000E cryostat (Leica, Nussloch, Germany), and thaw-mounted onto poly-L-lysine-coated glass slides. To visualize MCs, the sections were fixed with carnoy's fixative, and immersed in toluidine blue using the following protocol: carnoy's fixative for 1 min, RNase-free water for 10 sec, toluidine blue (0.5% in 0.12N hydrochloric acid) for 5 sec, RNase-free water for 10 sec, 70% ethanol for 15 sec, and 100% ethanol for 15 sec three times; the sections were then vacuumed for 10 min to dry. Each single MC was microdissected from the sections using a patch pipette, and 15 cells were collected with an LCM Cap using the PixCell Ile Laser Capture Microdissection System (Arcturus, Mountain View, CA). As a negative control, LCM Caps just put on tissue sections without MCs were subjected to the same protocols (no cell). Fifteen microdissected MCs were homogenized in denaturing buffer of RNeasy mini kits. Twenty nanograms of poly G (Sigma, Saint Louis, MO) was added to the lysate as a nucleic acid carrier, and total RNA was extracted. Fifty picograms of BMMC total RNA (BMMC-amp) and total RNAs extracted from sMCs in the stomach submucosa, mMCs in the stomach mucosa and skin MCs in the ear dermis were amplified and labeled using the three-round amplification method, and were hybridized to U74Av2 Murine Genome Array (Affymetrix). On the other hand, total RNA of BMMCs (BMMC-std) and peritoneal MC, which were collected from mouse peritoneal cavities and purified by density gradient centrifugation using metrizamide, were labeled and hybridized by the standard protocol. Raw microarray data of macrophages (E-MEXP-38/298290452) and fibroblasts (E-GEOD-6697/1629511747) using the standard protocol were obtained from ArrayExpress, a public repository for transcriptomics data. We used either microarray suite 5.0 of Affymetrix GeneChip Operating Software or the robust multi-array average (RMA) expression measure for log transformation (log2) and normalization of the GeneChip data [40, 41]. To determine the similarity in the data, hierarchical clustering analysis and PCA using the R statistical environment http://www.r-project.org were performed as a visualization technique. For comparison of the expression profiles of sMCs with that of mMCs, we selected 1,272 genes identified as having significantly different expression levels by the Limma's t-test (p < 0.05, n = 3). Signal values of sMCs and mMCs were normalized by the signal values of BMMCs. Using the k-means clustering algorithm, these genes were classified into seven clusters on the basis of similarity of their expression profiles.
Real-time reverse-transcription polymerase chain reaction (RT-PCR)
List of primers used for real-time PCR analysis.
Forward primer (5' -> 3')
Reverse primer (5' -> 3')
For tissue staining, frozen sections were fixed in 4% formaldehyde and incubated with a rabbit anti-Notch4 antibody (1:20, Santa Cruz Biotechnology, Santa Cruz, CA) or a rabbit anti-Ptgr1 antibody (1:20) which was a kind gift from Prof. Takao Shimizu (University of Tokyo) .
bone marrow-derived mast cell
submucosa mast cell
laser capture microdissection
mucosa mast cell
principal component analysis
robust multi-array average
reverse transcription-polymerase chain reaction.
This work was supported by Grants-in-Aid for Scientific Research on Priority Areas "Applied Genomics" from the Ministry of Education, Science, Sports, and Culture of Japan and from the Ministry of Health and Labor of Japan. We thank Dr. K Nakayama (Kyoto University) for their invaluable advice on this study. We appreciate Drs. T Shimizu and T Yokomizo for providing an anti-Ptgr1 antibody and generous instructions. We also thank Dr. HA Popiel and Ms. Y Nakaminami for careful reading and secretary assistance, respectively.
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