Identification of secreted proteins associated with obesity and type 2 diabetes in Psammomys obesus Bolton, K, Segal, D, McMillan, J, Sanigorski, A, Collier, G and Walder, K 2009, Identification of secreted proteins associated with obesity and type 2 diabetes in Psammomys obesus, International journal of obesity, vol. 33, pp. 1-13, doi: 10.1038/ijo.2009.148. Attached Files Name Description MIMEType Size Downloads Title Identification of secreted proteins associated with obesity and type 2 diabetes in Psammomys obesus Author(s) Bolton, K orcid.org/0000-0001-6721-4503 Segal, D McMillan, J Sanigorski, A orcid.org/0000-0002-2858-4621 Collier, G Walder, K orcid.org/0000-0002-6758-4763 Journal name International journal of obesity Volume number 33 Start page 1 End page 13 Total pages 13 Publisher Nature Publishing Group Place of publication Hampshire, England Publication date 2009-07-28 ISSN 0307-0565 1476-5497 Keyword(s) signal sequence trap secreted proteins psammomys obesus periostin type 2 diabetes diabetes obesity Summary 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 (B6%) 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. Notes International Journal of Obesity advance online publication, 28 July 2009; doi:10.1038/ijo.2009.148 Language eng DOI 10.1038/ijo.2009.148 Field of Research 060199 Biochemistry and Cell Biology not elsewhere classified Socio Economic Objective 920104 Diabetes HERDC Research category C1 Refereed article in a scholarly journal HERDC collection year 2009 Copyright notice ©2009, Macmillan Publishers Limited Persistent URL http://hdl.handle.net/10536/DRO/DU:30019851 Document type: Journal Article Collections: Faculty of Health School of Medicine Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Wed, 23 Sep 2009, 14:57:14 EST Fri, 25 Sep 2009, 08:25:32 EST Fri, 25 Sep 2009, 12:06:57 EST Fri, 25 Sep 2009, 12:09:39 EST Thu, 15 Oct 2009, 09:27:28 EST Wed, 01 Feb 2012, 16:10:30 EST Wed, 01 Feb 2012, 16:11:26 EST Wed, 07 Mar 2012, 10:06:52 EST Wed, 07 Mar 2012, 10:10:10 EST Mon, 16 Jun 2014, 13:07:50 EST Fri, 17 Oct 2014, 09:53:50 EST Mon, 19 Jan 2015, 10:55:11 EST Fri, 06 Feb 2015, 10:29:45 EST Thu, 07 Nov 2019, 06:39:50 EST Fri, 11 Mar 2022, 17:36:41 EST Filtered Full Citation counts:   Cited 14 times in TR Web of Science Cited 16 times in Scopus Search Google Scholar Access Statistics: 1343 Abstract Views, 4 File Downloads  -  Detailed Statistics Created: Wed, 23 Sep 2009, 14:57:12 EST by Sally Morrigan