Arabidopsis thaliana proteomics: from proteome to genome

Proteomics has become an important approach for investigating cellular processes and network functions. Significant improvements have been made during the last few years in technologies for high-throughput proteomics, both at the level of data analysis software and mass spectrometry hardware. As proteomics technologies advance and become more widely accessible, efforts of cataloguing and quantifying full proteomes are underway to complement other genomics approaches, such as RNA and metabolite profiling. Of particular interest is the application of proteome data to improve genome annotation and to include information on post-translational protein modifications with the annotation of the corresponding gene. This type of analysis requires a paradigm shift because amino acid sequences must be assigned to peptides without relying on existing protein databases. In this review, advances and current limitations of full proteome analysis are briefly highlighted using the model plant Arabidopsis thaliana as an example. Strategies to identify peptides are also discussed on the basis of MS/MS data in a protein database-independent approach.     

A streamlined approach to high-throughput proteomics

Proteomics has rapidly become an important tool for life science research, allowing the integrated analysis of global protein expression from a single experiment. To accommodate the complexity and dynamic nature of any proteome, researchers must use a combination of disparate protein biochemistry techniques, often a highly involved and time-consuming process. Whilst highly sophisticated, individual technologies for each step in studying a proteome are available, true high-throughput proteomics that provides a high degree of reproducibility and sensitivity has been difficult to achieve. The development of high-throughput proteomic platforms, encompassing all aspects of proteome analysis and integrated with genomics and bioinformatics technology, therefore represents a crucial step for the advancement of proteomics research. ProteomIQ? (Proteome Systems) is the first fully integrated, start-to-finish proteomics platform to enter the market. Sample preparation and tracking, centralized data acquisition and instrument control, and direct interfacing with genomics and bioinformatics databases are combined into a single suite of integrated hardware and software tools, facilitating high reproducibility and rapid turnaround times. This review will highlight some features of ProteomIQ, with particular emphasis on the analysis of proteins separated by 2D polyacrylamide gel electrophoresis.     

A streamlined approach to high-throughput proteomics

Proteomics has rapidly become an important tool for life science research, allowing the integrated analysis of global protein expression from a single experiment. To accommodate the complexity and dynamic nature of any proteome, researchers must use a combination of disparate protein biochemistry techniques, often a highly involved and time-consuming process. Whilst highly sophisticated, individual technologies for each step in studying a proteome are available, true high-throughput proteomics that provides a high degree of reproducibility and sensitivity has been difficult to achieve. The development of high-throughput proteomic platforms, encompassing all aspects of proteome analysis and integrated with genomics and bioinformatics technology, therefore represents a crucial step for the advancement of proteomics research. ProteomIQ (Proteome Systems) is the first fully integrated, start-to-finish proteomics platform to enter the market. Sample preparation and tracking, centralized data acquisition and instrument control, and direct interfacing with genomics and bioinformatics databases are combined into a single suite of integrated hardware and software tools, facilitating high reproducibility and rapid turnaround times. This review will highlight some features of ProteomIQ, with particular emphasis on the analysis of proteins separated by 2D polyacrylamide gel electrophoresis.     

pFind: a novel database-searching software system for automated peptide and protein identification via tandem mass spectrometry

SUMMARY: Research in proteomics requires powerful database-searching software to automatically identify protein sequences in a complex protein mixture via tandem mass spectrometry. In this paper, we describe a novel database-searching software system called pFind (peptide/protein Finder), which employs an effective peptide-scoring algorithm that we reported earlier. The pFind server is implemented with the C++ STL, .Net and XML technologies. As a result, high speed and good usability of the software are achieved.     

A Bioinformatics Perspective on Proteomics: Data Storage, Analysis, and Integration

The field of proteomics is advancing rapidly as a result of powerful new technologies and proteomics experiments yield a vast and increasing amount of information. Data regarding protein occurrence, abundance, identity, sequence, structure, properties, and interactions need to be stored. Currently, a common standard has not yet been established and open access to results is needed for further development of robust analysis algorithms. Databases for proteomics will evolve from pure storage into knowledge resources, providing a repository for information (meta-data) which is mainly not stored in simple flat files. This review will shed light on recent steps towards the generation of a common standard in proteomics data storage and integration, but is not meant to be a comprehensive overview of all available databases and tools in the proteomics community.     

Protein–protein interaction networks improve the proteomics data interpretation in induced apoptosis

Evaluation of: Deighton RF, Kerr LE, Short DM et al. Network generation enhances interpretation of proteomics data from induced apoptosis. Proteomics DOI: 10.1002/pmic.200900112 (2010) (Epub ahead of print).

The huge ongoing improvements in proteomics technologies, including the development of high-throughput mass spectrometry, are resulting in ever increasing information on protein behavior during cellular processes. The exponential accumulation of proteomics data has the promise to advance biomedical sciences by shedding light on the most important events that regulate mammalian cells under normal and pathophysiological conditions. This may provide practical insights that will impact medical practice and therapy, and may permit the development of a new generation of personalized therapeutics. Proteomics, as a powerful tool, creates numerous opportunities as well as challenges. At the different stages, data interpretation requires proteomics analysis, various tools to help deal with large proteomics data banks and the extraction of more functional information. Network analysis tools facilitate proteomics data interpretation and predict protein functions, functional interactions and in silica identification of intracellular pathways. The work reported by Deighton and colleagues illustrates an example of improving proteomics data interpretation by network generation. The authors used ingenuity pathway analysis to generate a protein network predicting direct and indirect interaction between 13 proteins found to be affected by staurosporine treatment. Importantly, the authors highlight the caution required when interpreting the results from a small number of proteins analyzed using network analysis tools.     

Clinical proteomics: present and future prospects

Advances in proteomics technology offer great promise in the understanding and treatment of the molecular basis of disease. The past decade of proteomics research, the study of dynamic protein expression, post-translational modifications, cellular and sub-cellular protein distribution, and protein-protein interactions, has culminated in the identification of many disease-related biomarkers and potential new drug targets. While proteomics remains the tool of choice for discovery research, new innovations in proteomic technology now offer the potential for proteomic profiling to become standard practice in the clinical laboratory. Indeed, protein profiles can serve as powerful diagnostic markers, and can predict treatment outcome in many diseases, in particular cancer. A number of technical obstacles remain before routine proteomic analysis can be achieved in the clinic; however the standardisation of methodologies and dissemination of proteomic data into publicly available databases is starting to overcome these hurdles. At present the most promising application for proteomics is in the screening of specific subsets of protein biomarkers for certain diseases, rather than large scale full protein profiling. Armed with these technologies the impending era of individualised patient-tailored therapy is imminent. This review summarises the advances in proteomics that has propelled us to this exciting age of clinical proteomics, and highlights the future work that is required for this to become a reality.     

Oncoproteomics: current trends and future perspectives

Oncoproteomics is the application of proteomics technologies in oncology. Functional proteomics is a promising technique for the rational identification of biomarkers and novel therapeutic targets for cancers. Recent progress in proteomics has opened new avenues for tumor-associated biomarker discovery. With the advent of new and improved proteomics technologies, such as the development of quantitative proteomic methods, high-resolution, -speed and -sensitivity mass spectrometry and protein arrays, as well as advanced bioinformatics for data handling and interpretation, it is now possible to discover biomarkers that can reliably and accurately predict outcomes during cancer management and treatment. However, there are several difficulties in the study of proteins/peptides that are not inherent in the study of nucleic acids. New challenges arise in large-scale proteomic profiling when dealing with complex biological mixtures. Nevertheless, oncoproteomics offers great promise for unveiling the complex molecular events of tumorigenesis, as well as those that control clinically important tumor behaviors, such as metastasis, invasion and resistance to therapy. In this review, the development and advancement of oncoproteomics technologies for cancer research in recent years are expounded.     

Proteomic technologies in modern biomedical science

This review highlights modern technologies employed in proteomics. Methods of sample preparations are discussed with special emphasis on the requirements for preparation of biological material, which may seriously influence the results of proteomic studies. Methods of solubilization, electrophoresis, chromatographic protein separation, and visualization of protein spots in gels are described. Modern methods of mass spectrometry used in proteomic studies include combination of protein chips with mass spectrometry. The review also describes approaches of functional proteomics, i.e., interactomics, and also bioinformatic resources used in proteomics for image analysis of 2D-gel-electrophoresis and for identification of protein sequences by mass spectra.     

Protein micro- and macroarrays: digitizing the proteome

The early applications of microarrays and detection technologies have been centered on DNA-based applications. The application of array technologies to proteomics is now occurring at a rapid rate. Numerous researchers have begun to develop technologies for the creation of microarrays of protein-based screening tools. The stability of antibody molecules when bound to surfaces has made antibody arrays a starting point for proteomic microarray technology. To minimize disadvantages due to size and availability, some researchers have instead opted for antibody fragments, antibody mimics or phage display technology to create libraries for protein chips. Even further removed from antibodies are libraries of aptamers, which are single-stranded oligonucleotides that express high affinity for protein molecules. A variation on the theme of protein chips arrayed with antibody mimics or other protein capture ligand is that of affinity MS where the protein chips are directly placed in a mass spectrometer for detection. Other approaches include the creation of intact protein microarrays directly on glass slides or chips. Although many of the proteins may likely be denatured, successful screening has been demonstrated. The investigation of protein-protein interactions has formed the basis of a technique called yeast two-hybrid. In this method, yeast "bait" proteins can be probed with other yeast "prey" proteins fused to DNA binding domains. Although the current interpretation of protein arrays emphasizes microarray grids of proteins or ligands on glass slides or chips, 2-D gels are technically macroarrays of authentic proteins. In an innovative departure from the traditional concept of protein chips, some researchers are implementing microfluidic printing of arrayed chemistries on individual protein spots blotted onto membranes. Other researchers are using in-jet printing technology to create protein microarrays on chips. The rapid growth of proteomics and the active climate for new technology is driving a new generation of companies and academic efforts that are developing novel protein microarray techniques for the future.     

Application of immobilized metal affinity chromatography in proteomics

It has been proved that the progress of proteomics is mostly determined by the development of advanced and sensitive protein separation technologies. Immobilized metal affinity chromatography (IMAC) is a powerful protein fractionation method used to enrich metal-associated proteins and peptides. In proteomics, IMAC has been widely employed as a prefractionation method to increase the resolution in protein separation. The combination of IMAC with other protein analytical technologies has been successfully utilized to characterize metalloproteome and post-translational modifications. In the near future, newly developed IMAC integrated with other proteomic methods will greatly contribute to the revolution of expression, cell-mapping and structural proteomics.     

Tackling the plant proteome: practical approaches, hurdles and experimental tools

The study of complex biological questions through comparative proteomics is becoming increasingly attractive to plant biologists as the rapidly expanding plant genomic and expressed sequence tag databases provide improved opportunities for protein identification. This review focuses on practical issues associated with comparative proteomic analysis, including the challenges of effective protein extraction and separation from plant tissues, the pros and cons of two-dimensional gel-based analysis and the problems of identifying proteins from species that are not recognized models for functional genomic studies. Specific points are illustrated using data from an ongoing study of the tomato and pepper fruit proteomes.     

Proteomics in reproductive biology: Beacon for unraveling the molecular complexities

Proteomics, an interface of rapidly evolving advances in physics and biology, is rapidly developing and expanding its potential applications to molecular and cellular biology. Application of proteomics tools has contributed towards identification of relevant protein biomarkers that can potentially change the strategies for early diagnosis and treatment of several diseases. The emergence of powerful mass spectrometry-based proteomics technique has added a new dimension to the field of medical research in liver, heart diseases and certain forms of cancer. Most proteomics tools are also being used to study physiological and pathological events related to reproductive biology. There have been attempts to generate the proteomes of testes, sperm, seminal fluid, epididymis, oocyte, and endometrium from reproductive disease patients. Here, we have reviewed proteomics based investigations in humans over the last decade, which focus on delineating the mechanism underlying various reproductive events such as spermatogenesis, oogenesis, endometriosis, polycystic ovary syndrome, embryo development. The challenge is to harness new technologies like 2-DE, DIGE, MALDI-MS, SELDI-MS, MUDPIT, LC–MS etc., to a greater extent to develop widely applicable clinical tools in understanding molecular aspects of reproduction both in health and disease.     

Molecular biologist's guide to proteomics.

The emergence of proteomics, the large-scale analysis of proteins, has been inspired by the realization that the final product of a gene is inherently more complex and closer to function than the gene itself. Shortfalls in the ability of bioinformatics to predict both the existence and function of genes have also illustrated the need for protein analysis. Moreover, only through the study of proteins can posttranslational modifications be determined, which can profoundly affect protein function. Proteomics has been enabled by the accumulation of both DNA and protein sequence databases, improvements in mass spectrometry, and the development of computer algorithms for database searching. In this review, we describe why proteomics is important, how it is conducted, and how it can be applied to complement other existing technologies. We conclude that currently, the most practical application of proteomics is the analysis of target proteins as opposed to entire proteomes. This type of proteomics, referred to as functional proteomics, is always driven by a specific biological question. In this way, protein identification and characterization has a meaningful outcome. We discuss some of the advantages of a functional proteomics approach and provide examples of how different methodologies can be utilized to address a wide variety of biological problems.     

Molecular Biologist's Guide to Proteomics

The emergence of proteomics, the large-scale analysis of proteins, has been inspired by the realization that the final product of a gene is inherently more complex and closer to function than the gene itself. Shortfalls in the ability of bioinformatics to predict both the existence and function of genes have also illustrated the need for protein analysis. Moreover, only through the study of proteins can posttranslational modifications be determined, which can profoundly affect protein function. Proteomics has been enabled by the accumulation of both DNA and protein sequence databases, improvements in mass spectrometry, and the development of computer algorithms for database searching. In this review, we describe why proteomics is important, how it is conducted, and how it can be applied to complement other existing technologies. We conclude that currently, the most practical application of proteomics is the analysis of target proteins as opposed to entire proteomes. This type of proteomics, referred to as functional proteomics, is always driven by a specific biological question. In this way, protein identification and characterization has a meaningful outcome. We discuss some of the advantages of a functional proteomics approach and provide examples of how different methodologies can be utilized to address a wide variety of biological problems.     

Proteomics technologies and challenges

Proteomics is the study of proteins and their interactions in a cell. With the completion of the Human Genome Project, the emphasis is shifting to the protein compliment of the human organism. Because proteome reflects more accurately on the dynamic state of a cell, tissue, or organism, much is expected from proteomics to yield better disease markers for diagnosis and therapy monitoring. The advent of proteomics technologies for global detection and quantitation of proteins creates new opportunities and challenges for those seeking to gain greater understanding of diseases. High-throughput proteomics technologies combining with advanced bioinformatics are extensively used to identify molecular signatures of diseases based on protein pathways and signaling cascades. Mass spectrometry plays a vital role in proteomics and has become an indispensable tool for molecular and cellular biology. While the potential is great, many challenges and issues remain to be solved, such as mining low abundant proteins and integration of proteomics with genomics and metabolomics data. Nevertheless, proteomics is the foundation for constructing and extracting useful knowledge to biomedical research. In this review, a snapshot of contemporary issues in proteomics technologies is discussed.     

Database on Demand – An online tool for the custom generation of FASTA‐formatted sequence databases

In mass spectrometry‐based proteomics, most conventional search engines match spectral data to sequence databases. These search databases thus play a crucial role in the identification process. While search engines can derive peptides in silico from protein sequences, this is usually limited to standard digestion algorithms. Customized search databases that provide detailed control over the search space can vastly outperform such standard strategies, especially in gel‐free proteomics experiments. Here we present Database on Demand, an easy‐to‐use web tool that can quickly produce a wide variety of customized search databases.     

Challenges in mass spectrometry-based proteomics

During the last decade, protein analysis and proteomics have been established as new tools for understanding various biological problems. As the identification of proteins after classical separation techniques, such as two-dimensional gel electrophoresis, have become standard methods, new challenges arise in the field of proteomics. The development of "functional proteomics" combines functional characterization, like regulation, localization and modification, with the identification of proteins for deeper insight into cellular functions. Therefore, different mass spectrometric techniques for the analysis of post-translational modifications, such as phosphorylation and glycosylation, have been established as well as isolation and separation methods for the analysis of highly complex samples, e.g. protein complexes or cell organelles. Furthermore, quantification of protein levels within cells is becoming a focus of interest as mass spectrometric methods for relative or even absolute quantification have currently not been available. Protein or genome databases have been an essential part of protein identification up to now. Thus, de novo sequencing offers new possibilities in protein analytical studies of organisms not yet completely sequenced. The intention of this review is to provide a short overview about the current capabilities of protein analysis when addressing various biological problems.