Zone-specific gene expression of mandibular condylar cartilage : biological implications of regional differences

Abstract

Mandibular condylar cartilage (MCC) consists of fibrous (F), proliferative (P), mature (M) and hypertrophic (H) zones, and exhibits distinctive biological features in physiology and function. Accordingly, the genetic regulation of MCC is expected to be different from other articular cartilages. Combined lasercapture microdissection (LCM) and microarray analysis (MAA) approach allows large-scale screening of zone-specific gene expressions. A few investigators have attempted to apply this approach on different cartilages, but not on MCC yet. Therefore, this study aimed to: 1) optimize an LCM protocol for isolating homogenous cell populations from MCC zones; 2) perform a zone-specific comprehensive gene expression analysis for MCC using LCM & MAA; and 3) find a set of genes, following the validation of MAA data using in-vivo and invitro quantitative reverse transcription-polymerase chain reaction (qRT-PCR), which could potentially distinguish MCC zones from each other and from articular chondrocytes.

MCC and femoral condylar cartilage (FCC) specimens were harvested from normal 5-week-old SD rats, and formalin-fixed sections and cryosections were compared histologically. LCM samples for five groups (FCC and four MCC zones) were prepared, and then RNAs were extracted and evaluated for integrity. For MAA experiment, LCM samples were amplified before microarray hybridization. MAA data were analyzed using GeneSpring software. cDNA from unamplified LCM-RNA samples were also prepared for the five groups for in-vivo qRT-PCR validation of 48 genes selected from MAA data, 10 of which were additionally validated by cultivating ATDC5 cells and extracting RNA at different time points for in-vitro qRT-PCR validation.

Factors enhancing tissue visualization, LCM efficiency, LCM specificity, and RNA yield and integrity were optimized in the suggested LCM protocol. At a 2-fold change, 8353 (26.86%) transcripts were differentially expressed among the MCC zones and FCC. Subsequent data mining allowed the creation of seven subsets of 127 genes. Forty-eight genes were selected for validation based on their signal intensities, clustering classification, and gene ontology. In-vivo and in-vitro qRT-PCR showed high consistency with the MAA data. Results revealed robust gene expression differences among MCC zones, and between articular chondrocytes and MCC cells. The F & P zones could be characterized by upregulation of Crabp1, Dpt, Fndc1, Aspn, Tnmd, Bcl11b, Angptl1, Col14a1, and downregulation of Mug1, Foxa2, Lect1, and Matn3. Opposite modulation of the same genes may characterize M & H zones. In addition, unizonal distinct profiles were also identified; upregulated Igfbp6, Igha, Hils1, and Ptgds genes might be considered as potential markers for F, P, M, and H zones, respectively. In conclusion, this study sets up an LCM protocol that enables isolating homogenous zone-specific cell populations from the MCC, and obtaining highquality RNAs for subsequent gene expression analysis. Comprehensive gene profiling has been successfully achieved with high fidelity; using minute RNA amounts via the LCM & MAA combined approach. The MCC cells clearly exhibit distinguishable phenotypes from the articular chondrocytes, and a set of genes has been determined as potential unizonal/bizonal markers to identify MCC zones. Generating accurate regional data enhances our understanding of MCC biology and provides invaluable insights for tissue-engineering and cellbased therapeutic strategies.