tailieunhanh - Báo cáo y học: "A semi-quantitative GeLC-MS analysis of temporal proteome expression in the emerging nosocomial pathogen Ochrobactrum anthrop"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Critical Care giúp cho các bạn có thêm kiến thức về ngành y học đề tài: A semi-quantitative GeLC-MS analysis of temporal proteome expression in the emerging nosocomial pathogen Ochrobactrum anthropi. | Open Access A semi-quantitative GeLC-MS analysis of temporal proteome expression in the emerging nosocomial pathogen Ochrobactrum anthropi Robert Leslie James Graham Mohit K Sharma Nigel G Ternan D Brent Weatherly Rick L Tarleton and Geoff McMullan Addresses School of Biomedical Sciences University of Ulster Coleraine County Londonderry BT52 1SA UK. The Center for Tropical and Emerging Global Diseases University of Georgia Athens GA 30605 USA. Correspondence Robert Leslie James Graham. Email Published 13 June 2007 Genome Biology 2007 8 R110 doi gb-2007-8-6-rl 10 The electronic version of this article is the complete one and can be found online at http 2007 8 6 R110 Received 16 March 2007 Revised 10 May 2007 Accepted l3 June 2007 2007 Graham et al. licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Background The a-Proteobacteria are capable of interaction with eukaryotic cells with some members such as Ochrobactrum anthropi capable of acting as human pathogens. O. anthropi has been the cause of a growing number of hospital-acquired infections however little is known about its growth physiology and metabolism. We used proteomics to investigate how protein expression of this organism changes with time during growth. Results This first gel-based liquid chromatography-mass spectrometry GeLC-MS temporal proteomic analysis of O. anthropi led to the positive identification of 131 proteins. These were functionally classified and physiochemically characterized. Utilizing the emPAI protocol to estimate protein abundance we assigned molar concentrations to all proteins and thus were able to identify 19 with significant changes in their expression. Pathway reconstruction led to the