Download Free Implementation Of Chemical Protein Nucleic Acid Cross Linking Into Mass Spectrometric Workflows And Mass Spectrometric Database Searches Book in PDF and EPUB Free Download. You can read online Implementation Of Chemical Protein Nucleic Acid Cross Linking Into Mass Spectrometric Workflows And Mass Spectrometric Database Searches and write the review.

Protein nucleic acid interactions play a pivotal role in cells, from transcription to translation. Functions of proteins in protein nucleic acid interactions are diverse: histones are responsible for the packaging of the genomic DNA; ribosomal proteins are part of the ribosome, which is responsible for protein synthesis. Crosslinking mass spectrometry proved to be a useful tool to identify protein-nucleic acid interactions and their dynamics in the cell. A vast amount of effort has been spent to elucidate protein-nucleic acid interactions with UV crosslinking mass spectrometry, whereas chem...
A novel protocol for the study of protein-nucleic acid interactions is presented and demonstrated to be feasible. The protocol combines photochemical crosslinking techniques and mass spectrometric methods into a new strategy for identifying protein domains or amino acid residues that are in close contact with nucleic acid in protein-nucleic acid complexes. Identifying nucleic acid binding domains in proteins provides a starting point for understanding structure-function relationships in protein-nucleic acid complexes. The protocol can be divided into three parts: 1) Cross linking of the protein-nucleic acid complex by irradiation with ultraviolet light and subsequently verifying the crosslinking by mass spectrometry; 2) Mass spectrometric peptide mapping of crosslinked protein-nucleic acid complexes to identify crosslinked peptide-nucleic acid hybrids; 3) Tandem mass spectrometric sequencing of peptide-nucleic acid hybrids to localize the crosslinked amino acid residue(s). The experimental data described in this dissertation documents our efforts to establish and implement this analytical protocol. Using several different protein-nucleic acid systems and different crosslinking techniques, we have demonstrated the feasibility of a mass spectrometric based approach to structurally characterize UV-crosslinked protein-nucleic acid complexes. Matrix-assisted laser desorption/ionization mass spectrometry was for the first time demonstrated to be highly effective for detection and molecular weight determination of intact, UV-crosslinked protein-nucleic acid complexes and for molecular weight determination of synthetic and UV-crosslinked peptide-nucleic acid hybrids. Electrospray ionization mass spectrometry and tandem mass spectrometry was demonstrated to be effective for analysis of synthetic peptide-nucleic acid hybrids and, in conjunction with HPLC, for peptide mapping of a protein. The first application of MALDI mass spectrometry to the characterization of crosslinked peptide-nucleic acid hybrids isolated from a photochemically crosslinked protein-nucleic acid complex demonstrate that the new protocol can be used to identify nucleic acid binding domains in proteins.
The field of proteomics has developed rapidly over the past decade nurturing the need for a detailed introduction to the various informatics topics that underpin the main liquid chromatography tandem mass spectrometry (LC-MS/MS) protocols used for protein identification and quantitation. Proteins are a key component of any biological system, and monitoring proteins using LC-MS/MS proteomics is becoming commonplace in a wide range of biological research areas. However, many researchers treat proteomics software tools as a black box, drawing conclusions from the output of such tools without considering the nuances and limitations of the algorithms on which such software is based. This book seeks to address this situation by bringing together world experts to provide clear explanations of the key algorithms, workflows and analysis frameworks, so that users of proteomics data can be confident that they are using appropriate tools in suitable ways.
Protein-nucleic acid interactions are a key part of essential cellular processes and their disturbance often results in the development of diseases. Crosslinking mass spectrometry (XL-MS)-based approaches have become increasingly popular for the proteome-wide discovery of nucleic acid-binding proteins. The basic principle of the methodology relies on covalent attachment of proteins and binding nucleic acids by crosslinking, which makes the heteroconjugates amenable to MS analysis. Building up on comprehensive nucleic acid-binding protein inventories, there is an increasing demand for higher...
Bottom-up proteomics has emerged as a powerful technology for biological studies. The technique is used for a myriad of purposes, including among others protein identification, post-translational modification identification, protein-protein interaction analysis, protein quantification analysis, and protein structure analysis. The data analysis approaches of bottom-up proteomics have evolved over the past two decades, and many different algorithms and software programs have been developed for these varied purposes. In this thesis, I have focused on improving the database search strategies for the important special applications of bottom-up proteomics, including cross-linking mass spectrometry proteomics and O-glycoproteomics. In cross-linking mass spectrometry proteomics, a sample of proteins is treated with a chemical cross-linking reagent. This causes peptides within the proteins to be cross-linked to one another, forming peptide doublets that are released by treatment of the sample with a protease such as trypsin. The data analysis tools are designed to identify the cross-linked peptides. In O-glycoproteomics, the peptides that are released by protease digestion of the protein sample can be modified with any of or even multiple distinct O-glycans, and the data analysis tools should be able to identify all of the glycans and the modification sites at which they are located. In both cases, traditional database searching strategies which try to match the experimental spectra to all potential theoretical spectra is not practical due to the large increases in search space. Researchers suffered from a lack of efficient data analysis tools for these two applications. Here we successfully devised new search algorithms to address these problems, and impemented them in two new software modules in our laboratories' bottom-up software engine MetaMorpheus (Crosslinking data analysis via MetaMorpheusXL and O-glycoproteomics data analysis via O-Pair Search). The new search strategies used in the software program are both based on ion-indexed open search, which was first developed for large scale proteomic studies in the programs MSFragger and Open-pFind. The ion-indexed open search was optimized for cross-linking mass spectrometry proteomics and O-glycoproteomics in this study, and combined with other algorithms. In O-glycoproteomics, a graph-based algorithm is used to speed up the identification and localization of O-glycans. Other useful features have been added in the software program, such as enabling analysis of both cleavable cross-links and non-cleavable cross-links in the cross-link search module, and calculating localization probabilities in the O-glyco search module. Further optimizations including machine learning methods for false discovery rate (FDR) analysis, retention time prediction and spectral prediction could further improve the current best search approaches for cross-link proteomics and O-glycoproteomics data analysis. Chapter 1 provides an overview of bottom-up proteomics data analysis methods and outlines how ion-indexed open search could be useful for special bottom-up proteomics studies. Chapter 2 describes the development of a cross-linking mass spectrometry proteomics search module, resulting in efficiency improvements for both cleavable and non-cleavable cross-link proteomics data analysis. Chapter 3 describes the development of an O-glycoproteomics search module; by combining the ion-indexed open search algorithm with the graph-based localization algorithm, the O-pair Search is more than 2000 times faster than the currently widely used software program Byonic. In Chapter 4, a novel top-down data acquisition method is described. Chapter 5 provides conclusions and future directions.
Bottom-up proteomics has emerged as a powerful technology for biological studies. The technique is used for a myriad of purposes, including among others protein identification, post-translational modification identification, protein-protein interaction analysis, protein quantification analysis, and protein structure analysis. The data analysis approaches of bottom-up proteomics have evolved over the past two decades, and many different algorithms and software programs have been developed for these varied purposes. In this thesis, I have focused on improving the database search strategies for the important special applications of bottom-up proteomics, including cross-linking mass spectrometry proteomics and O-glycoproteomics. In cross-linking mass spectrometry proteomics, a sample of proteins is treated with a chemical cross-linking reagent. This causes peptides within the proteins to be cross-linked to one another, forming peptide doublets that are released by treatment of the sample with a protease such as trypsin. The data analysis tools are designed to identify the cross-linked peptides. In O-glycoproteomics, the peptides that are released by protease digestion of the protein sample can be modified with any of or even multiple distinct O-glycans, and the data analysis tools should be able to identify all of the glycans and the modification sites at which they are located. In both cases, traditional database searching strategies which try to match the experimental spectra to all potential theoretical spectra is not practical due to the large increases in search space. Researchers suffered from a lack of efficient data analysis tools for these two applications. Here we successfully devised new search algorithms to address these problems, and impemented them in two new software modules in our laboratories' bottom-up software engine MetaMorpheus (Crosslinking data analysis via MetaMorpheusXL and O-glycoproteomics data analysis via O-Pair Search). The new search strategies used in the software program are both based on ion-indexed open search, which was first developed for large scale proteomic studies in the programs MSFragger and Open-pFind. The ion-indexed open search was optimized for cross-linking mass spectrometry proteomics and O-glycoproteomics in this study, and combined with other algorithms. In O-glycoproteomics, a graph-based algorithm is used to speed up the identification and localization of O-glycans. Other useful features have been added in the software program, such as enabling analysis of both cleavable cross-links and non-cleavable cross-links in the cross-link search module, and calculating localization probabilities in the O-glyco search module. Further optimizations including machine learning methods for false discovery rate (FDR) analysis, retention time prediction and spectral prediction could further improve the current best search approaches for cross-link proteomics and O-glycoproteomics data analysis. Chapter 1 provides an overview of bottom-up proteomics data analysis methods and outlines how ion-indexed open search could be useful for special bottom-up proteomics studies. Chapter 2 describes the development of a cross-linking mass spectrometry proteomics search module, resulting in efficiency improvements for both cleavable and non-cleavable cross-link proteomics data analysis. Chapter 3 describes the development of an O-glycoproteomics search module; by combining the ion-indexed open search algorithm with the graph-based localization algorithm, the O-pair Search is more than 2000 times faster than the currently widely used software program Byonic. In Chapter 4, a novel top-down data acquisition method is described. Chapter 5 provides conclusions and future directions.
Presents Practical Applications of Mass Spectrometry for Protein Analysis and Covers Their Impact on Accelerating Drug Discovery and Development Covers both qualitative and quantitative aspects of Mass Spectrometry protein analysis in drug discovery Principles, Instrumentation, Technologies topics include MS of peptides, proteins, and ADCs , instrumentation in protein analysis, nanospray technology in MS protein analysis, and automation in MS protein analysis Details emerging areas from drug monitoring to patient care such as Identification and validation of biomarkers for cancer, targeted MS approaches for biomarker validation, biomarker discovery, and regulatory perspectives Brings together the most current advances in the mass spectrometry technology and related method in protein analysis
Cross-linking mass spectrometry maps the structural topology of protein complexes by using the distance between linked residues as spatial constraints, complementing other structural biology techniques. However, the identification of cross-linked peptides scales poorly with the number of proteins analyzed. Our lab has previously developed MS-cleavable cross-linkers to enable the separation of cross-linked peptides prior to sequencing, enabling peptide identifica- tion using standard peptide search databases. We describe the design and implementation of platform and application named XLTools for the automated identification of MS-cleavable cross-linked peptides. XLTools supports open and proprietary data formats and common peptide search databases, facilitating its integration into existing workflows. Furthermore, we developed peak-picking and validation algorithms to enable the accurate quantitation of cross-linked peptides in complex samples. We demonstrate the application of XLTools to the quantitative analysis of the 26S proteasome cross-linked in vivo and in vitro.
76 2. Short Oligonucleotide Mass Analysis 76 2. 1. Method Outline 76 2. 2. Design of PCR Primers and Fragments for Analysis 78 2. 3. Typical PCR Reaction Conditions 79 3. Electrospray Ionisation Mass Spectrometry 79 Formation of Ions 3. 1. 79 3. 2. Tandem Mass Spectrometry 79 3. 3. Typical ESI-MS Settings for SOMA 80 4. Purification Procedures 80 4. 1. Phenol/Chloroform Extraction and Ethanol Precipitation 80 4. 2. In-line HPLC Purification 81 5. Genotyping Using SOMA 81 5. 1. APC Genotyping in Human Subjects 81 5. 2. APC Genotyping in Min Mice 85 5. Mutation Detection Using SOMA 86 6. 1. Analysis of p53 Mutations in Liver Cancer Patients 86 6. 1. 1. p53 Mutations in Liver Tumours 87 6. 1. 2. p53 Mutations in Plasma Samples 88 7. Advantages and Disadvantages of SOMA 89 8. Future Perspectives 90 9. Acknowledgements 91 10. References 91 CHAPTER 7 WV. Bienvenut, M. Müller, PM. Palagi, E. Gasteiger, M. Heller, E. Jung, M. Giron, R. Gras, S. Gay, PA. Binz, G J. Hughes, JC. Sanchez, RD. Appel, DF. Hochstrasser Proteomics and Mass Spectrometry: Some Aspects and Recent Developments 1. Introduction to Proteomics 93 2. Protein Biochemical and Chemical Processing Followed by Mass Spectrometric Analysis 94 2. 1. 2-DE Gel Protein Separation 95 Protein Identification Using Peptide Mass Fingerprinting and Robots 96 2. 2. 2. 2. 1. MALDI-MS Analysis 98 2. 2. 2. MS/MS Analysis 102 Improvement of the Identification by Chemical Modification of Peptides 106 2. 2. 3.