OBJECTIVE: Skeletal muscle produces a variety of secreted proteins that have important roles in intercellular communication and affects processes such as glucose homoeostasis. The objective of this study was to develop a novel Signal Sequence Trap (SST) in conjunction with cDNA microarray technology to identify proteins secreted from skeletal muscle of Psammomys obesus that were associated with obesity and type 2 diabetes (T2D). DESIGN: Secreted proteins that were differentially expressed between lean, normal glucose tolerant (NGT), overweight and impaired glucose tolerant (IGT) and obese, T2D P. obesus were isolated using SST in conjunction with cDNA microarray technology. Subsequent gene expression was measured in tissues from P. obesus by real-time PCR (RT-PCR). RESULTS: The SST yielded 1600 positive clones, which were screened for differential expression. A total of 91 (approximately 6%) clones were identified by microarray to be differentially expressed between NGT, IGT and T2D P. obesus. These clones were sequenced to identify 51 genes, of which only 27 were previously known to encode secreted proteins. Three candidate genes not previously associated with obesity or type 2 diabetes, sushi domain containing 2, collagen and calcium-binding EGF domains 1 and periostin (Postn), as well as one gene known to be associated, complement component 1, were shown by RT-PCR to be differentially expressed in skeletal muscle of P. obesus. Further characterization of the secreted protein Postn revealed it to be predominantly expressed in adipose tissue, with higher expression in visceral compared with subcutaneous adipose depots. CONCLUSION: SST in conjunction with cDNA microarray technology is a powerful tool to identify differentially expressed secreted proteins involved in complex diseases such as obesity and type 2 diabetes. Furthermore, a number of candidate genes were identified, in particular, Postn, which may have a role in the development of obesity and type 2 diabetes.
OBJECTIVE: Skeletal muscle produces a variety of secreted proteins that have important roles in intercellular communication and affects processes such as glucose homoeostasis. The objective of this study was to develop a novel Signal Sequence Trap (SST) in conjunction with cDNA microarray technology to identify proteins secreted from skeletal muscle of Psammomys obesus that were associated with obesity and type 2 diabetes (T2D). DESIGN: Secreted proteins that were differentially expressed between lean, normal glucose tolerant (NGT), overweight and impaired glucose tolerant (IGT) and obese, T2D P. obesus were isolated using SST in conjunction with cDNA microarray technology. Subsequent gene expression was measured in tissues from P. obesus by real-time PCR (RT-PCR). RESULTS: The SST yielded 1600 positive clones, which were screened for differential expression. A total of 91 (approximately 6%) clones were identified by microarray to be differentially expressed between NGT, IGT and T2D P. obesus. These clones were sequenced to identify 51 genes, of which only 27 were previously known to encode secreted proteins. Three candidate genes not previously associated with obesity or type 2 diabetes, sushi domain containing 2, collagen and calcium-binding EGF domains 1 and periostin (Postn), as well as one gene known to be associated, complement component 1, were shown by RT-PCR to be differentially expressed in skeletal muscle of P. obesus. Further characterization of the secreted protein Postn revealed it to be predominantly expressed in adipose tissue, with higher expression in visceral compared with subcutaneous adipose depots. CONCLUSION: SST in conjunction with cDNA microarray technology is a powerful tool to identify differentially expressed secreted proteins involved in complex diseases such as obesity and type 2 diabetes. Furthermore, a number of candidate genes were identified, in particular, Postn, which may have a role in the development of obesity and type 2 diabetes.
Authors: Niko Braun; Kontheari Sen; M Dominik Alscher; Peter Fritz; Martin Kimmel; Johann Morelle; Eric Goffin; Achim Jörres; Rudolf P Wüthrich; Clemens D Cohen; Stephan Segerer Journal: Perit Dial Int Date: 2013-02-01 Impact factor: 1.756
Authors: Nadia J T Roumans; Roel G Vink; Marij Gielen; Maurice P Zeegers; Claus Holst; Ping Wang; Arne Astrup; Wim H Saris; Armand Valsesia; Jörg Hager; Marleen A van Baak; Edwin C M Mariman Journal: Genes Nutr Date: 2015-11-19 Impact factor: 5.523