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.     

Use of proteomics to understand seed development in rice

Rice is an important cereal crop and has become a model monocot for research into crop biology. Rice seeds currently feed more than half of the world's population and the demand for rice seeds is rapidly increasing because of the fast‐growing world population. However, the molecular mechanisms underlying rice seed development is incompletely understood. Genetic and molecular studies have developed our understanding of substantial proteins related to rice seed development. Recent advancements in proteomics have revolutionized the research on seed development at the single gene or protein level. Proteomic studies in rice seeds have provided the molecular explanation for cellular and metabolic events as well as environmental stress responses that occur during embryo and endosperm development. They have also led to the new identification of a large number of proteins associated with regulating seed development such as those involved in stress tolerance and RNA metabolism. In the future, proteomics, combined with genetic, cytological, and molecular tools, will help to elucidate the molecular pathways underlying seed development control and help in the development of valuable and potential strategies for improving yield, quality, and stress tolerance in rice and other cereals. Here, we reviewed recent progress in understanding the mechanisms of seed development in rice with the use of proteomics.     

Protein nanocrystallography: a new approach to structural proteomics

This article describes a new approach to structural proteomics that can produce and characterize diffracting, stable and radiation-resistant crystals of miniscule dimensions using nanotechnology. We believe that the protein microcrystals obtained by nanotechnology-based protein thin-film template crystallization, as well as groundbreaking technology, such as atomic force microscopy, nanogravimetry and synchrotron microfocus, have enabled protein nanocrystallography to be defined as a unique technology capable of forming and characterizing stable protein microcrystals down to atomic resolution. A new route from art to science and technology has, therefore, been opened in protein crystallography, and it could be used to unravel the mysteries of many systems that remain unsolved.     

A proteomics approach to understanding protein ubiquitination

There is a growing need for techniques that can identify and characterize protein modifications on a large or global scale. We report here a proteomics approach to enrich, recover, and identify ubiquitin conjugates from Saccharomyces cerevisiae lysate. Ubiquitin conjugates from a strain expressing 6xHis-tagged ubiquitin were isolated, proteolyzed with trypsin and analyzed by multidimensional liquid chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) for amino acid sequence determination. We identified 1,075 proteins from the sample. In addition, we detected 110 precise ubiquitination sites present in 72 ubiquitin-protein conjugates. Finally, ubiquitin itself was found to be modified at seven lysine residues providing evidence for unexpected diversity in polyubiquitin chain topology in vivo. The methodology described here provides a general tool for the large-scale analysis and characterization of protein ubiquitination.     

Application of mass spectrometry based proteomics to understand diabetes: A special focus on interactomics

Diabetes, a multifactorial disorder is characterized by elevated blood glucose levels resulting from changes in lifestyle, genetic and epigenetic changes or aberrations in proteome. In addition, alterations in post-translational modifications (PTMs) and protein-protein interactions (PPIs) also contribute to the development of diabetes pathogenesis. Recent advances in omics technologies have broadened the perspective for systematic investigation of proteome alterations in understanding the pathogenesis of diabetes. Further, PPIs are central to cellular signaling in all living organisms and deranged PPIs lead to diabetic complications. In this context, affinity purification mass spectrometry (AP-MS) along with diverse bioinformatic approaches has proven to be competent in mapping large-scale PPI networks around the critical players in the glucose homeostasis. In this review, we revisit the application of proteomic approaches in investigating proteome alterations and probing PPI networks for a better understanding of the underlying intricacies of the major signaling pathways in altered glucose homeostasis.     

A multi-scale approach to understand the mechanobiology of intermediate filaments

The animal cell cytoskeleton consists of three interconnected filament systems: actin microfilaments, microtubules and the lesser known intermediate filaments (IFs). All mature IF proteins share a common tripartite domain structure and the ability to assemble into 8–12 nm wide filaments. At the time of their discovery in the 1980s, IFs were only considered as passive elements of the cytoskeleton mainly involved in maintaining the mechanical integrity of tissues. Since then, our knowledge of IFs structure, assembly plan and functions has improved dramatically. Especially, single IFs show a unique combination of extensibility, flexibility and toughness that is a direct consequence of their unique assembly plan. In this review we will first discuss the mechanical design of IFs by combining the experimental data with recent multi-scale modeling results. Then we will discuss how mechanical forces may interact with IFs in vivo both directly and through the activation of other proteins such as kinases.     

Protein phosphatases: a genomic outlook to understand their function in plants

Protein phosphatases are the vital regulatory components of various signal transduction pathways in eukaryotes. Signaling pathways triggered during stress and development have been regulated by different classes of protein phosphatases in plants. Recently, genome-wide expressional analysis in Arabidopsis and crop plant such as rice revealed differential expression pattern for several protein phosphatases under different abiotic stresses, in various tissues and at different developmental stages. This expression pattern could be extrapolated to the possible function of protein phosphatases in abiotic stress signaling and tolerance, and during plant development. Here, we discuss organisation and expression patterns of members of the protein phosphatase gene family, and their potential functional role in plants.     

A proteomics approach to identify the ubiquitinated proteins in mouse heart

There is a growing need for the large-scale identification of the ubiquitinated proteins and ubiquitin attachment sites. As part of this effort, we generated a transgenic mouse expressing a tagged ubiquitin in the heart. We found that the majority of ubiquitinated proteins in mouse heart are insoluble in detergent-free buffer and were chemically cleaved after methionine with CNBr. CNBr cleaved the proteins into smaller polypeptides while preserving the ubiquitin chains. Ubiquitin-conjugated polypeptides were then purified under denaturing conditions, digested with Lys-C and trypsin, and analyzed by liquid chromatography-tandem mass spectrometry. We identified 121 proteins that were ubiquitinated in mouse heart, and we detected 33 ubiquitination sites in 21 of the proteins. Components of cardiac muscle and many mitochondrial proteins were identified as substrates for ubiquitination, strongly suggesting that proteins related to major heart functions such as contraction and energy production are under continuous quality control by the ubiquitin system.     

A metal-coded affinity tag approach to quantitative proteomics

The quantitative analysis of protein mixtures is pivotal for the understanding of variations in the proteome of living systems. Therefore, approaches have been recently devised that generally allow the relative quantitative analysis of peptides and proteins. Here we present proof of concept of the new metal-coded affinity tag (MeCAT) technique, which allowed the quantitative determination of peptides and proteins. A macrocyclic metal chelate complex (1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA)) loaded with different lanthanides (metal(III) ions) was the essential part of the tag. The combination of DOTA with an affinity anchor for purification and a reactive group for reaction with amino acids constituted a reagent that allowed quantification of peptides and proteins in an absolute fashion. For the quantitative determination, the tagged peptides and proteins were analyzed using flow injection inductively coupled plasma MS, a technique that allowed detection of metals with high precision and low detection limits. The metal chelate complexes were attached to the cysteine residues, and the course of the labeling reaction was followed using SDS-PAGE and MALDI-TOF MS, ESI MS, and inductively coupled plasma MS. To limit the width in isotopic signal spread and to increase the sensitivity for ESI analysis, we used the monoisotopic lanthanide macrocycle complexes. Peptides tagged with the reagent loaded with different metals coelute in liquid chromatography. In first applications with proteins, the calculated detection limit for bovine serum albumin for example was 110 amol, and we have used MeCAT to analyze proteins of the Sus scrofa eye lens as a model system. These data showed that MeCAT allowed quantification not only of peptides but also of proteins in an absolute fashion at low concentrations and in complex mixtures.     

A proteomics approach to identifying fish cell lines

Fish cell lines are relatively easy to culture and most have simple growth requirements that make cross contamination a potential problem. Cell line contamination is not an uncommon incident in laboratories handling more than one cell line and many reports have been made on cross contamination of mammalian cell lines. Although problems of misidentification and cross-contamination of fish cell lines have rarely been reported, these are issues of concern for cell culturists that can make scientific results and their reproducibility unreliable. Proper identification of cell lines is thus crucial and protocols for routine and rapid screening are preferred. Cytogenetic evaluation, DNA fingerprinting, microsatellite analysis and PCR methods have been published for inter-species identification of many cell lines, but discerning intra-species contamination has been challenging. More complex DNA fingerprinting and hybridization techniques coupled with isoenzyme analysis have been developed to discriminate intra-species contamination, however, these require complex and time consuming procedures to enable cell identification thus are difficult to apply for routine use. A simple proteomic approach has been made to identify several fish cell lines derived from tissues of the same or differing species. Protein expression signatures (PES) of the evaluated fish cell lines have been developed using 2-DE and image analysis. A higher degree of concordance was seen among cell lines derived from rainbow trout, than from other fish species. Similar concordance was seen in cells derived from the same tissues than from other tissues within the same species. These profiles have been saved in an electronic databank and could be made available to be used for discerning the origins of the various cell lines evaluated. This proteomic approach could thus serve as an additional, valuable and reliable technique for the identification of fish cell lines.     

A coarse-grained approach to protein design: learning from design to understand folding

Computational studies have given a great contribution in building our current understanding of the complex behavior of protein molecules; nevertheless, a complete characterization of their free energy landscape still represents a major challenge. Here, we introduce a new coarse-grained approach that allows for an extensive sampling of the conformational space of a large number of sequences. We explicitly discuss its application in protein design, and by studying four representative proteins, we show that the method generates sequences with a relatively smooth free energy surface directed towards the target structures.     

A proteomics approach to investigate the process of Zn hyperaccumulation in Noccaea caerulescens (J & C. Presl) F.K. Meyer

Zinc (Zn) is an essential trace element in all living organisms, but is toxic in excess. Several plant species are able to accumulate Zn at extraordinarily high concentrations in the leaf epidermis without showing any toxicity symptoms. However, the molecular mechanisms of this phenomenon are still poorly understood. A state‐of‐the‐art quantitative 2D liquid chromatography/tandem mass spectrometry (2D‐LC‐MS/MS) proteomics approach was used to investigate the abundance of proteins involved in Zn hyperaccumulation in leaf epidermal and mesophyll tissues of Noccaea caerulescens. Furthermore, the Zn speciation in planta was analyzed by a size‐exclusion chromatography/inductively coupled plasma mass spectrometer (SEC‐ICP‐MS) method, in order to identify the Zn‐binding ligands and mechanisms responsible for Zn hyperaccumulation. Epidermal cells have an increased capability to cope with the oxidative stress that results from excess Zn, as indicated by a higher abundance of glutathione S‐transferase proteins. A Zn importer of the ZIP family was more abundant in the epidermal tissue than in the mesophyll tissue, but the vacuolar Zn transporter MTP1 was equally distributed. Almost all of the Zn located in the mesophyll was stored as Zn–nicotianamine complexes. In contrast, a much lower proportion of the Zn was found as Zn–nicotianamine complexes in the epidermis. However, these cells have higher concentrations of malate and citrate, and these organic acids are probably responsible for complexation of most epidermal Zn. Here we provide evidence for a cell type‐specific adaptation to excess Zn conditions and an increased ability to transport Zn into the epidermal vacuoles.     

Protein microarray: A key approach of proteomics

Proteins are vital parts of living organisms, for they consist of the main components of physiological metabolic pathways. The expression and modification status of proteins in cells are time- and space-dependent based upon functions as well as responses to stress. A subject aiming at understanding of protein status under certain physiological condition in a large scale, termed proteomics, is fundamentally important in life science. Although the proteomic investigation mainly relies on electrophoresis, liquid chromatography, and mass spectrometry, protein microarray is emerging as one of new techniques, and its power is being recognized in the field recently. Herein, we highlight progress in protein microarray, both its generation and application.     

A proposal for using the ensemble approach to understand genetic regulatory networks

Understanding the genetic regulatory network comprising genes, RNA, proteins and the network connections and dynamical control rules among them, is a major task of contemporary systems biology. I focus here on the use of the ensemble approach to find one or more well-defined ensembles of model networks whose statistical features match those of real cells and organisms. Such ensembles should help explain and predict features of real cells and organisms. More precisely, an ensemble of model networks is defined by constraints on the "wiring diagram" of regulatory interactions, and the "rules" governing the dynamical behavior of regulated components of the network. The ensemble consists of all networks consistent with those constraints. Here I discuss ensembles of random Boolean networks, scale free Boolean networks, "medusa" Boolean networks, continuous variable networks, and others. For each ensemble, M statistical features, such as the size distribution of avalanches in gene activity changes unleashed by transiently altering the activity of a single gene, the distribution in distances between gene activities on different cell types, and others, are measured. This creates an M-dimensional space, where each ensemble corresponds to a cluster of points or distributions. Using current and future experimental techniques, such as gene arrays, these M properties are to be measured for real cells and organisms, again yielding a cluster of points or distributions in the M-dimensional space. The procedure then finds ensembles close to those of real cells and organisms, and hill climbs to attempt to match the observed M features. Thus obtains one or more ensembles that should predict and explain many features of the regulatory networks in cells and organisms.