The serine protease inhibitor trappin-2 is present in cartilage and synovial fluid in osteoarthritis

OBJECTIVE

Trappins are small serine protease inhibitors bound to extracellular matrix (ECM) through the actions of transglutaminase (TGase) enzymes. Trappin-2 is present in many tissues and is upregulated at sites of injury. In osteoarthritis (OA), serine proteases contribute to articular cartilage destruction, and TGase activity is increased. Yet little is known about matrix-bound serine protease inhibitors or TGase substrates in articular cartilage. Our purpose was to determine if trappin-2 was present in OA cartilage and synovial fluid (SF).

METHODS

OA knee articular cartilage and SF were assayed for trappin-2 protein by Western blotting, ELISA, and immunohistochemistry. Trappin-2 mRNA was detected with RT-PCR. The ECM components bound to trappin-2 were identified by 2-D gel electrophoresis and peptide fingerprinting.

RESULTS

Trappin-2 was detectable in OA articular cartilage extracts, cultured chondrocytes, conditioned media, and SF by Western blotting. OA cartilage protein extracts contained significantly higher quantities of trappin-2 than normal cartilage protein extracts (22.98 +/- 1.28 ng/mg wet weight vs 14.97 +/- 1.92 ng/mg wet weight; p < 0.01). RT-PCR confirmed the presence of trappin-2 mRNA in OA chondrocytes. Immunohistochemical studies of OA cartilage revealed trappin-2 protein in chondrocytes. Peptide mapping of trappin-2 binding partners showed that fibromodulin was bound to trappin-2 in cartilage.

CONCLUSION

We confirmed the presence of trappin-2 in OA cartilage and SF. Elevated levels of TGase activity in OA cartilage may increase levels of this serine protease inhibitor in response to injury.

ChromSorter PC: a database of chromosomal regions associated with human prostate cancer

BACKGROUND

Our increasing use of genetic and genomic strategies to understand human prostate cancer means that we need access to simplified and integrated information present in the associated biomedical literature. In particular, microarray gene expression studies and associated genetic mapping studies in prostate cancer would benefit from a generalized understanding of the prior work associated with this disease. This would allow us to focus subsequent laboratory studies to genomic regions already related to prostate cancer by other scientific methods. We have developed a database of prostate cancer related chromosomal information from the existing biomedical literature. The input material was based on a broad literature search with subsequent hand annotation of information relevant to prostate cancer.

DESCRIPTION

The database was then analyzed for identifiable trends in the whole scale literature. We have used this database, named ChromSorter PC, to present graphical summaries of chromosomal regions associated with prostate cancer broken down by age, ethnicity and experimental method. In addition we have placed the database information on the human genome using the Generic Genome Browser tool that allows the visualization of the data with respect to user generated datasets.

CONCLUSIONS

We have used this database as an additional dataset for the filtering of genes identified through genetics and genomics studies as warranting follow-up validation studies. We would like to make this dataset publicly available for use by other groups. Using the Genome Browser allows for the graphical analysis of the associated data http://www.prostategenomics.org/datamining/chrom-sorter_pc.html. Additional material from the database can be obtained by contacting the authors (mdatta@mcw.edu).