Current strategies for quantitative proteomics

Applications of Proteomic Tools to Study Insect Vector-Plant Virus Interactions

Proteins are crucial players of biological interactions within and between the organisms and thus it is important to understand the role of proteins in successful partnerships, such as insect vectors and their plant viruses. Proteomic approaches have identified several proteins at the interface of virus acquisition and transmission by their insect vectors which could be potential molecular targets for sustainable pest and viral disease management strategies. Here we review the proteomic techniques used to study the interactions of insect vector and plant virus. Our review will focus on the techniques available to identify the infection, global changes at the proteome level in insect vectors, and protein-protein interactions of insect vectors and plant viruses. Furthermore, we also review the integration of other techniques with proteomics and the available bioinformatic tools to analyze the proteomic data.

Methods and approaches for the comprehensive characterization and quantification of cellular proteomes using mass spectrometry

Proteomics has been proposed as one of the key technologies in the postgenomic era. So far, however, the comprehensive analysis of cellular proteomes has been a challenge because of the dynamic nature and complexity of the multitude of proteins in cells and tissues. Various approaches have been established for the analyses of proteins in a cell at a given state, and mass spectrometry (MS) has proven to be an efficient and versatile tool. MS-based proteomics approaches have significantly improved beyond the initial identification of proteins to comprehensive characterization and quantification of proteomes and their posttranslational modifications (PTMs). Despite these advances, there is still ongoing development of new technologies to profile and analyze cellular proteomes more completely and efficiently. In this review, we focus on MS-based techniques, describe basic approaches for MS-based profiling of cellular proteomes and analysis methods to identify proteins in complex mixtures, and discuss the different approaches for quantitative proteome analysis. Finally, we briefly discuss novel developments for the analysis of PTMs. Altered levels of PTM, sometimes in the absence of protein expression changes, are often linked to cellular responses and disease states, and the comprehensive analysis of cellular proteome would not be complete without the identification and quantification of the extent of PTMs of proteins.

Comparison of protein expression by isotope-coded affinity tag labeling

Isotope-coded affinity tag (ICAT) labeling, in combination with mass spectrometry (MS), has been widely adopted as an effective method for comparing protein abundance levels. This chapter describes the ICAT labeling procedure in search for the celecoxib-regulated proteins in a colon cancer cell line. Celecoxib, a cyclooxygenase-2 (COX-2) specific inhibitor, is used as a colorectal cancer preventative drug in clinical trials. Here, celecoxib is used to inhibit the expression of COX-2 in a colon cancer cell line HT-29. To elucidate the proteomic changes induced by celecoxib, the protein lysates from the treated and control cells are prepared. The cysteine-containing proteins are labeled with the heavy and light ICAT reagents, respectively. The labeled proteins are then combined and digested with trypsin. The ICAT-labeled peptides are subject to the purification through an avidin column and eventually the cleavage of the biotin tags. This chapter focuses on the ICAT labeling procedure itself, because sample preparation is the most critical step of an ICAT-based protein expression comparison experiment. Other related procedures such as the cation exchange high performance liquid chromatography separation of peptides and MS analysis are detailed elsewhere in this book.

Proteomic strategies to elucidate pathogenic mechanisms of spirochetes

Spirochetes are a unique group of bacteria that include several motile and highly invasive pathogens that cause a multitude of acute and chronic disease processes. Nine genomes of spirochetes have been completed, which provide significant insights into pathogenic mechanisms of disease and reflect an often complex lifestyle associated with a wide range of environmental and host factors encountered during disease transmission and infection. Characterization of the outer membrane of spirochetes is of particular interest since it interacts directly with the host and environs during disease and likely contains candidate vaccinogens and diagnostics. In concert with appropriate fractionation techniques, the tools of proteomics have rapidly evolved to characterize the proteome of spirochetes. Of greater significance, studies have confirmed the differential expression of many proteins, including those of the outer membrane, in response to environmental signals encountered during disease transmission and infection. Characterization of the proteome in response to such signals provides novel insights to understand pathogenic mechanisms of spirochetes.

Proteolytic 18O-labeling strategies for quantitative proteomics

A number of proteomic techniques have been developed to quantify proteins in biological systems. This review focuses on the quantitative proteomic technique known as "proteolytic 18O-labeling." This technique utilizes a protease and H(2)18O to produce labeled peptides, with subsequent chromatographic and mass spectrometric analysis to identify and quantify (relative) the proteins from which the peptides originated. The technique determines the ratio of individual protein's expression level between two samples relative to each other, and can be used to quantitatively examine protein expression (comparative proteomics) and post-translational modifications, and to study protein-protein interactions. The present review discusses various aspects of the 18O-labeling technique, including: its history, the advantages and disadvantages of the proteolytic 18O-labeling technique compared to other techniques, enzymatic considerations, the problem of variable incorporation of 18O atoms into peptides with a discussion on recent advancements of the technique to overcome it, computational tools to interpret the data, and a review of the biological applications.

Advances in the analysis of dynamic protein complexes by proteomics and data processing

Signal transduction governs virtually every cellular function of multicellular organisms, and its deregulation leads to a variety of diseases. This intricate network of molecular interactions is mediated by proteins that are assembled into complexes within individual signaling pathways, and their composition and function is often regulated by different post-translational modifications. Proteomic approaches are commonly used to analyze biological complexes and networks, but often lack the specificity to address the dynamic and hence transient nature of the interactions and the influence of the multiple post-translational modifications that govern these processes. Here we review recent developments in proteomic research to address these limitations, and discuss several technologies that have been developed for this purpose. The synergy between these proteomic and computational tools, when applied together with global methods to the analysis of individual proteins, complexes and pathways, may allow researchers to unravel the underlying mechanisms of signaling networks in greater detail than previously possible.

Difference in Mass Analysis Using Labeled Lysines (DIMAL-K)

Here we describe an original strategy for unbiased quantification of protein expression called difference in mass analysis using labeled lysine (K) (DIMAL-K). DIMAL-K is based on the differential predigestion labeling of lysine residues in complex protein mixtures. The method is relevant for proteomic analysis by two-dimensional electrophoresis and MALDI-TOF mass spectrometry. Protein labeling on lysine residues uses two closely related chemical reagents, S-methyl thioacetimidate and S-methyl thiopropionimidate. Using protein standards, we demonstrated that 1) the chemical labeling was quantitative, specific, and rapid; 2) the differentially labeled proteins co-migrated on two-dimensional gels; and 3) the identification by mass fingerprinting and the relative quantification of the proteins were possible from a single MALDI-TOF mass spectrum. The power of the method was tested by comparing and quantifying the secretion of proteins in normal and proinflammatory astrocytic secretomes (20 microg). We showed that DIMAL-K was more sensitive and accurate than densitometric image analysis and allowed the detection and quantification of novel proteins.

Comprehensive post-genomic data analysis approaches integrating biochemical pathway maps

Post-genomic era research is focusing on studies to attribute functions to genes and their encoded proteins, and to describe the regulatory networks controlling metabolic, protein synthesis and signal transduction pathways. To facilitate the analysis of experiments using post-genomic technologies, new concepts for linking the vast amount of raw data to a biological context have to be developed. Visual representations of pathways help biologists to understand the complex relationships between components of metabolic networks, and provide an invaluable resource for the integration of transcriptomics, proteomics and metabolomics data sets. Besides providing an overview of currently available bioinformatic tools for plant scientists, we introduce BioPathAt, a newly developed visual interface that allows the knowledge-based analysis of genome-scale data by integrating biochemical pathway maps (BioPathAtMAPS module) with a manually scrutinized gene-function database (BioPathAtDB) for the model plant Arabidopsis thaliana. In addition, we discuss approaches for generating a biochemical pathway knowledge database for A. thaliana that includes, in addition to accurate annotation, condensed experimental information regarding in vitro and in vivo gene/protein function.

Subtle modification of isotope ratio proteomics; an integrated strategy for expression proteomics

Use of minor modification of isotope ratio to code samples for expression proteomics is being investigated. Alteration of (13)C abundance to approximately 2% yields a measurable effect on peptide isotopic distribution and inferred isotope ratio. Elevation of (13)C abundance to 4% leads to extension of isotopic distribution and background peaks across every unit of the mass range. Assessment of isotope ratio measurement variability suggests substantial contributions from natural measurement variability. A better understanding of this variable will allow assessment of the contribution of sequence dependence. Both variables must be understood before meaningful mixing experiments for relative expression proteomics are performed. Subtle modification of isotope ratio ( approximately 1-2% increase in (13)C) had no effect upon either the ability of data-dependent acquisition software or database searching software to trigger tandem mass spectrometry or match MSMS data to peptide sequences. More severe modification of isotope ratio caused a significant drop in performance of both functionalities. Development of software for deconvolution of isotope ratio concomitant with protein identification using LC-MSMS, or any other proteomics strategy, is underway (Isosolv). The identified peptide sequence is then be used to provide elemental composition for accurate isotope ratio decoding and the potential to control for specific amino acid biases should these prove significant. It is suggested that subtle modification of isotope ratio proteomics (SMIRP) offers a convenient approach to in vivo isotope coding of plants and might ultimately be extended to mammals including humans.

Towards a systems biology understanding of human health: Interplay between genotype, environment and nutrition

Sequencing of the human genome has opened the door to the most exciting new era for the holistic system description of human health. It is now possible to study the underlying mechanisms of human health in relation to diet and other environmental factors such as drugs and toxic pollutants. Technological advances make it feasible to envisage that in the future personalized drug treatment and dietary advice and possibly tailored food products can be used for promoting optimal health on an individual basis, in relation to genotype and lifestyle. Life-Science research has in the past very much focused on diseases and how to reestablish human health after illness. Today, the role of food and nutrition in human health and especially prevention of illness is gaining recognition. Diseases of modern civilization, such as diabetes, heart disease and cancer have been shown to be effected by dietary patterns. The risk of disease is often associated with genetic polymorphisms, but the effect is dependent on dietary intake and nutritional status. To understand the link between diet and health, nutritional-research must cover a broad range of areas, from the molecular level to whole body studies. Therefore it provides an excellent example of integrative biology requiring a systems biology approach. The current state and implications of systems biology in the understanding of human health are reviewed. It becomes clear that a complete mechanistic description of the human organism is not yet possible. However, recent advances in systems biology provide a trajectory for future research in order to improve health of individuals and populations. Disease prevention through personalized nutrition will become more important as the obvious avenue of research in life sciences and more focus will need to be put upon those natural ways of disease prevention. In particular, the new discipline of nutrigenomics, which investigates how nutrients interact with humans, taking predetermined genetic factors into account, will mediate new insights into human health that will finally have significant positive impact on our quality of life.