Literature DB >> 11987127

Analysis of the proteome in the human pituitary.

Sarka Beranova-Giorgianni1, Francesco Giorgianni, Dominic M Desiderio.   

Abstract

The pituitary is the master endocrine gland responsible for the regulation of various physiologic and metabolic processes. Proteomics offers an efficient means for a comprehensive analysis of pituitary protein expression. This paper reports on the application of proteomics for the mapping of major proteins in a normal (control) pituitary. Pituitary proteins were separated by two-dimensional gel electrophoresis with immobilized pH 3-10 gradient strips. Major protein spots that were visualized in the two-dimensional gel by silver staining were excised, and the proteins in these spots were digested with trypsin. The tryptic digests were analyzed by mass spectrometry, and the mass spectrometric data were used to identify the proteins through searches of the SWISS-PROT or NCBInr protein sequence databases. The majority of the proteins were identified on the basis of peptide mass fingerprinting data obtained by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Several proteins were also characterized based on product-ion spectra measured by post-source decay analysis and/or liquid chromatography-electrospray-quadrupole ion trap mass spectrometry. To date, 62 prominent protein spots, corresponding to 38 different proteins, were identified. The identified proteins include important pituitary hormones, structural proteins, enzymes, and other proteins. The protein identification data were used to establish a two-dimensional reference database of the human pituitary, which can be accessed over the Internet (http://www.utmem.edu/proteomics). This database will serve as a tool for further proteomics studies of pituitary protein expression in health and disease.

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Year:  2002        PMID: 11987127     DOI: 10.1002/1615-9861(200205)2:5<534::AID-PROT534>3.0.CO;2-K

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  8 in total

1.  Phosphoproteomic analysis of the human pituitary.

Authors:  Sarka Beranova-Giorgianni; Yingxin Zhao; Dominic M Desiderio; Francesco Giorgianni
Journal:  Pituitary       Date:  2006       Impact factor: 4.107

2.  Optimized proteomic analysis of a mouse model of cerebellar dysfunction using amine-specific isobaric tags.

Authors:  Jun Hu; Jin Qian; Oleg Borisov; Sanqiang Pan; Yan Li; Tong Liu; Longwen Deng; Kenneth Wannemacher; Michael Kurnellas; Christa Patterson; Stella Elkabes; Hong Li
Journal:  Proteomics       Date:  2006-08       Impact factor: 3.984

3.  Proteomics and transcriptomics analyses of secretagogin down-regulation in human non-functional pituitary adenomas.

Authors:  Xianquan Zhan; Chheng-Orn Evans; Nelson M Oyesiku; Dominic M Desiderio
Journal:  Pituitary       Date:  2003       Impact factor: 4.107

Review 4.  Prognostic indicators in pituitary tumors.

Authors:  Agustinus Suhardja; Kalman Kovacs; Oded Greenberg; Bernd W Scheithauer; Ricardo V Lloyd
Journal:  Endocr Pathol       Date:  2005       Impact factor: 4.056

5.  Heterogeneity analysis of the proteomes in clinically nonfunctional pituitary adenomas.

Authors:  Xianquan Zhan; Xiaowei Wang; Ying Long; Dominic M Desiderio
Journal:  BMC Med Genomics       Date:  2014-12-24       Impact factor: 3.063

6.  Establishing a protein expression profile database for the normal human pituitary gland using two-dimensional high-performance liquid chromatography combined with LTQ-Orbitrap mass spectrometry.

Authors:  Rong Xie; Wei Xu; Weimin Bao; Hang Liu; Luping Chen; Yiwen Shen; Jianhong Zhu
Journal:  Neural Regen Res       Date:  2012-12-25       Impact factor: 5.135

7.  Targeting Nrf2-Mediated Oxidative Stress Response Signaling Pathways as New Therapeutic Strategy for Pituitary Adenomas.

Authors:  Xianquan Zhan; Jiajia Li; Tian Zhou
Journal:  Front Pharmacol       Date:  2021-03-24       Impact factor: 5.810

8.  TMT-based quantitative proteomics revealed follicle-stimulating hormone (FSH)-related molecular characterizations for potentially prognostic assessment and personalized treatment of FSH-positive non-functional pituitary adenomas.

Authors:  Ya Wang; Tingting Cheng; Miaolong Lu; Yun Mu; Biao Li; Xuejun Li; Xianquan Zhan
Journal:  EPMA J       Date:  2019-08-29       Impact factor: 6.543

  8 in total

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