Current Proteomics, Vol. 1, No. 1, 2004

Current Proteomics, Vol. 1, No. 1, 2004

Contents

CURRENT PROTEOMICS: A New Journal for the Publication of Review Articles on Proteomics Pp. 1-2

Deb N. Chakravarti

How Much of the Proteome Do We See with Discovery - Based Proteomics Methods and How Much Do We Need to See? Pp. 3-12

Scott D. Patterson

[Abstract] [Full text article]

New Paradigms in Cellular Function and the Need for Top-Down Proteomics Analysis Pp. 13-25

Corinne Stannard, Larry R. Brown, and Jasminka Godovac-Zimmermann

[Abstract] [Full text article]

Proteomics as a Tool to Study Microbial Interactions Pp. 27-34

Petter Melin

[Abstract] [Full text article]

Large Gel Two-Dimensional Electrophoresis: Improving Recovery of Cellular Proteome Pp. 35-39

Naoyuki Inagaki and Kazuhiro Katsuta

[Abstract] [Full text article]

Annotation of the Human Genome by High-Throughput Sequence Analysis of Naturally Occurring Proteins Pp. 41-48

Simon J. McGowan, Jonathan Terrett, Clive G. Brown, Paul J. Adam, Louise Aldridge, Jason C. Allen, Bob Amess, Kristian A. Andrews, Martin Barnes, David E. Barnwell, Joanne Berry, Helen Bird, Robert S. Boyd, Marissa J. Broughton, Alice Brown, Jim A. Bruce, Luc M. J. Brusten, Nicholas J. Draper, Beverley M. Elsmore , Colin D. Freeman, David M. Giles, Haiping Gong, Darren Gormley, Matthew R. Griffiths, Tim D.R. Hawkes, Paul S. Haynes, Kate J. Heesom, Athula Herath, Katherine Hollis, Lindsey J. Hudsen, Janet Inman, Merrill Jacobs, Darren Jarman, Imran Kibria, John J. Kilgour, Samuel K. Kinuthia, Kim E. Lane, Margaret L. Lees, Julie Loader, Andrew Longmore, Michael McEwan, Alice Middleton, Stephen Moore, Carol Murray, Helen M. Murray, C. Paul Myatt, Stanley S. Ng, Andrew O'Neil, Raj B. Parekh, Ashok Patel, Kaajal B. Patel, Sonal Patel, Thakor P. Patel, Robin J. Philp, Albert E. Platt, Helen Poyser, Cynthia Prendergast, Sally Prime, Nicholas Redpath, Mike Reeves, Andrew W. Robinson, Christian Rohlff, Jeffrey M. Rosenbaum, Martin Schenker, Elaine Scrivener, Nigel Shipston, Shaistah Siddiq, Christopher Southan, Daniel I. R. Spencer, Alasdair Stamps, Marc A. Steffens, David Stevenson, Gavin M.A. Sweetman, Stephen Taylor, Reid Townsend, Andrew M. Ventom, Martin N. H. Waller, Celia Weresch, Amanda M. Williams, Richard J. Woolliscroft, Xiaohong Yu and Andrew Lyall

[Abstract] [Full text article]

The Protein Data Bank: A Case Study in Management of Community Data Pp. 49-57

Helen M. Berman, Philip E. Bourne and John Westbrook

[Abstract] [Full text article]

Structural Proteomics: Inferring Function from Protein Structure Pp. 59-65

David L. Wild and Mansoor A. S. Saqi

[Abstract] [Full text article]

The Computational Versatility of Proteomic Signaling Networks Pp. 67-81

Herbert M. Sauro

[Abstract] [Full text article]

Abstracts

[Back to top] How Much of the Proteome Do We See with Discovery-Based Proteomics Methods and How Much Do We Need to See?

Scott D. Patterson

Despite the recent advances in parallel protein-based analyses the proportion of the protein composition of any specific tissue or organism that is currently being analyzed is still unknown. The ultimate aim of proteomics is to characterize all of the proteins in a biological system under study, but much has been gained from knowledge of smaller subsets of the proteome. Therefore, while techniques and instrumentation are being improved to increase the sensitivity of analysis, it is just as important to answer the question of what depth of analysis is required for reasonable conclusions to be reached. The questions to be answered and the resulting depth of analysis required will vary depending upon whether the understanding is required for diagnostic markers, therapeutic targets or biological systems. The issues associated with increasing the depth of analysis of proteins in the context of these areas will be discussed. However, it should be noted that merely increasing the amount of data acquired will not necessarily increase the amount of knowledge of a particular system and as such careful implementation of proteomic methods is required to advance these fields of research.

[Back to top] New Paradigms in Cellular Function and the Need for Top-Down Proteomics Analysis

Corinne Stannard, Larry R. Brown, and Jasminka Godovac-Zimmermann

New paradigms suggest that many aspects of cellular function are controlled by rapid, stochastic, combinatorial processes. The implications of these new paradigms for proteomics are considered in relation to the information content of top-down and bottom-up proteomics approaches. Functional evidence and current proteomics experiments suggest that phenotypic variation of individual proteins is a major form of control for the combinatorial processes and that in many cases top-down proteomics approaches will be essential for proteomics investigations of cellular function. It is suggested that the new paradigms and the nature of the general cellular processes that affect protein phenotypes should be taken into account in the development of proteomics methodology. More generally, the coupling of stochastic, combinatorial processes to energy-dependent processes that change protein phenotypes may represent one of the basic principles of cellular function.

[Back to top] Proteomics as a Tool to Study Microbial Interactions

Petter Melin

In microbial ecology, researchers have started to use a great variety of methods initially developed by molecular biologists. Mostly, these studies have dealt with microbial diversity in specific environments. Recently, new questions have been raised, e.g. what changes occur within a microbial community during competition or after a change in the surrounding environment? For this, molecular tools such as mRNA differential display, microarrays and proteomics can be employed. In this review, the use of proteomics for studies of microbial interactions is discussed. One aspect of competition between microbes can be simulated by treatment of one microbe with antibiotics produced by a competing microbe. A more complicated approach involves co-cultivation of the competitors. In order to reveal species-specific protein patterns, it is advisable to maintain the organisms separated. In a somewhat reversed experimental design, the target gene for an antibiotic is disrupted, and changes in the mutant proteome are subsequently screened for. Generally, a proteomic study will reveal proteins with both expected and surprising changes in abundance upon competition, but also previously unknown proteins are likely to be identified. It is obvious that most antibiotics can trigger secondary responses, which will result in a change of abundance of several proteins. However, an approach based on proteomics alone may not be sufficient to obtain a complete data set for describing microbial interactions. Therefore, further studies are necessary for proteins whose quantitative profile changes, e.g. by generating knockout strains for phenotypic analysis. Despite some inherent limitations, proteomics is a useful method, and an important complement to other approaches for studies of microbial interactions.

[Back to top] Large Gel Two-Dimensional Electrophoresis: Improving Recovery of Cellular Proteome

Naoyuki Inagaki and Kazuhiro Katsuta

One of the goals of expression proteomics is to display and analyze all the proteins in a particular proteome. Cells are thought to comprise tens of thousands of proteins expressed in a dynamic range of 1-10⁵ or 10⁶. Low recovery of cellular proteome leads to a gross loss of important proteins. Thus, proteomics demands a powerful technology that separates complex mixture of proteins including low abundant ones. In the case of two-dimensional gel electrophoresis (2-DE), enlargement of the gel size appears a straightforward and effective strategy for improving the recovery of cellular proteins. Multiple narrow pH range immobilized pH gradients (nrIPGs) and long isoelectric focusing (IEF) gels afford improved separation of proteins in the first dimension according to isoelectric point. In addition, multiple long SDS-PAGE gels of different polyacrylamide concentrations provide a tool to improve the resolution of the second dimension according to molecular weight. Recent data suggest that 2-DE with large gels can display more than 11,000 protein spots expressed in a 1-10⁵ dynamic range in cells.

[Back to top] Annotation of the Human Genome by High-Throughput Sequence Analysis of Naturally Occurring Proteins

The identification of protein-coding genes is currently based on the merging of evidence and predictions from a variety of databases that may themselves contain inaccurate and partial information. We have developed a method for mapping accurate interpretations of protein MS-MS data to the genome. This approach enables verification of genes, exons, transcripts and variant transcripts as well as the de novo discovery of novel protein-coding genes. Here we describe improvements in spectral interpretation algorithms, multiple separation techniques, sub-cellular fractionation and novel bioinformatics approaches to characterise more than 14,000 naturally occurring human genes.

[Back to top] The Protein Data Bank: A Case Study in Management of Community Data

Helen M. Berman, Philip E. Bourne and John Westbrook

As the sole repository for three-dimensional structure data of biological macro-molecules, the Protein Data Bank (PDB) is an important resource for research in the academic, pharmaceutical, and biotechnology sectors. Over the years, the methods and speed of structure determination have changed as technology has improved. At the same time the methods for data collection, archiving, and distribution of the structural data in the PDB have also evolved. Concurrently, the community of data depositors and users has expanded. As of October 2003, the PDB archive contains approximately 23,000 released structures and the website receives over 160,000 hits per day. The lessons learned from the development of the PDB may be applicable to the ongoing development of new data and knowledge resources in proteomics.

[Back to top] Structural Proteomics: Inferring Function from Protein Structure

David L. Wild and Mansoor A. S. Saqi

We describe how knowledge of three dimensional protein structure can add to the understanding of as yet functionally unannotated protein sequences. Structure determination may reveal that the new protein shares structural similarity with a previously observed structure or that it is a novel fold. The manner in which structure can be used to suggest the function of a protein will depend on the number and diversity of homologous sequences and the extent to which these sequences are functionally characterized. These factors are discussed with reference to a number of illustrative examples of structures solved by structural genomics initiatives.

[Back to top] The Computational Versatility of Proteomic Signaling Networks

Herbert M. Sauro

Almost all proteomic signaling networks in prokaryotes and eukaryotes are based on the simple phosphorylation/dephosporylation cycle; from this simple unit it is possible to construct a huge variety of control and computational circuits, both analog and digital. With the characterization of many signaling networks, researchers are turning to address the question of how a particular physiological response can be understood in terms of the proteins that make up the network; this is one of the central questions in “Systems Biology”. In this article I wish to summarize the great versatility of the basic protein cycle as a means to construct complex functional behaviors including the central role that feedback plays in determining the properties of protein based networks.