12国外大学研究所收集sanger chapter4.docx

2021-08-06 10:08:05558.2 KB27页 约4.91万字金币:100 点击下载

12国外大学研究所收集sanger chapter4.docx

12国外大学研究所收集sanger chapter4.docx
文本预览:4 Proteomic analysis of tissues4 Proteomic analysis of tissues from the streptomycin mousemodel and integration with transcriptomic data4.1Introduction4.1.1 Label-free mass spectrometry for large scale tissue proteomicsAdvances in the field of proteomics have vastly broadened potential applications in recent years, moving beyond simple protein identification to quantitative profiling of complex protein mixtures [232]. Early quantitative proteomic analysis involved two-dimensional gel separation of protein mixtures, with quantitation performed by comparison of stained protein spot volumes prior to protein identification by MS. Current technology permits quantitation at the MS level, giving rise to vast increases in specificity and accuracy, and allowing rapid analysis of large numbers of proteins. The two major approaches for quantification are stable isotope labelling and label-free analysis. Prior to recent advances stable isotope labelling achieved more accurate quantitation. In this approach separate samples labelled with amino acids containing different isotopes are analysed in a single MS run. However highly reproducible high pressure liquid chromatography (HPLC) systems and mass spectrometers have now been developed which allow highly accurate quantitation between separate runs [233]. Isotope labelling is expensive compared with label-free sample preparation and labelling strategies are unsuited to the analysis of tissue from whole organisms, therefore a label-free approach was employed in the proteomic analysis described herein. Figure 4.1outlines the approach used for the analysis of the murine caecal proteome.In shotgun proteomics proteins are digested into peptides which are then identified by MS, and the resultant catalogue of peptides is compared against a reference proteome to allow piecing back together of the original proteins in the sample. Analysis is most commonly performed by ‘data-dependent acquisition’ (DDA) in which precursor ions are selected for fragmentation inside the mass spectrometer on the basis of their abundance, and only a fixed number of precursor ions recorded in a survey scan are selected for fragmentation to determine peptide sequence. In this approach precursor ion selection is stochastic and a large proportion of the peptides present are not sampled. Therefore a DDA approach is not well- suited to the analysis of complex proteomes of whole tissue extracts. Data-independent acquisition (DIA) approaches utilise an unbiased strategy in which precursor ions arefragmented irrespective of intensity or other characteristics, producing a complete analysis of94precursor ions. Two major strategies have been described: SWATH-MS, and MSE developedprecursor ions. Two major strategies have been described: SWATH-MS, and MSE developed by Waters. SWATH-MS has been used to produce quantitative profiles of complex samples such as human colorectal cancer tumours, however this approach is limited by the requirement for a priori information about peptide fragment ion patterns and retention time which may not be available for the particular sample of interest [234, 235]. MSE approaches do not require such a library. MS scans are performed alternating between high and low collision energy for ion generation, and fragment ions are measured in the former while intact peptides are measured in the latter. Advanced data analysis software matches precursor peptides and fragment ions. Overall this new approach results in high sequence coveragerelative to DDA approaches [236-238].Over the past decade proteomic analysis has been applied in the quest for understanding of host-pathogen interactions, as reviewed in [239]. The majority of studies to date focussed on the pathogen proteome, for example numerous studies investigated the impact of growth conditions on the proteome of S. Typhimurium. In one such study Salmonella were sorted from tissue homogenates to characterise the proteome during infection of a mammalian host [240, 241]. The proteome of the host is comparatively much larger and contains a greater dynamic range in protein abundance, presenting a bigger challenge both in detection and quantitation of proteins, and in the interpretation of the resulting data. A small number of studies have investigated changes in the host proteome upon infection using cultured cell lines. In particular, in proteomic analysis of a macrophage cell line during infection with S. Typhimurium 1,006 macrophage proteins were detected, of which 24% were changed significantly during infection [242]. A similar study of an intestinal epithelial cell line during infection with EPEC detected over 2,000 host proteins of which 13% were differentially expressed upon infection [243]. Whilst macrophage proteins found to be altered in Salmonella infection were involved in diverse functions, epithelial cell proteins whose levels were affected by EPEC were mostly involved in actin dynamics, cell adhesion, G-protein signalling and ion transport. These studies are limited to investigation of early events in infection and fail to capture secreted proteins, an important functional category and one which experiences dramatic changes in infection [244]. To our knowledge no studies to date have sought to describe the effects of bacterial infection on the global host proteome atthe level of whole tissue in an in vivo infection.95ABFigure 4.1. Quantitative shotgun proteomics. (A) Outline of the process used for the MS analysis of mouse caecal tissue samples described in this chapter. A protocol for extraction of proteins from caecum was developed combiningABFigure 4.1. Quantitative shotgun proteomics. (A) Outline of the process used for the MS analysis of mouse caecal tissue samples described in this chapter. A protocol for extraction of proteins from caecum was developed combining detergent and heat for protein solublisation and denaturation. Purified extracted proteins were proteolytically fragmented using trypsin. HPLC was used to separate the complex mixture of peptides for MS analysis. Peptides were ionised on exit from the HPLC column, moving directly into the mass spectrometer for time of flight (TOF)-based detection of mass. (B) Diagram to illustrate the label-free intensity-based relative quantification method used in MS analysis described in this chapter. Individual biological samples were prepared separately and analysed sequentially by MS. Quantitation was based on the differential intensities of peptides of identical amino acid sequence and charge between separate MS runs. Δ in
展开>> 收起<<