Quantitative proteomic approach to study subcellular localization of membrane proteins

Proteomics technologies for the global identification and quantification of proteins

This review provides an introduction for the nonspecialist to proteomics and in particular the major approaches available for global protein identification and quantification. Proteomics technologies offer considerable opportunities for improved biological understanding and biomarker discovery. The central platform for proteomics is tandem mass spectrometry (MS) but a number of other technologies, resources, and expertise are absolutely required to perform meaningful experiments. These include protein separation science (and protein biochemistry in general), genomics, and bioinformatics. There are a range of workflows available for protein (or peptide) separation prior to tandem MS and subsequent bioinformatics analysis to achieve protein identifications. The predominant approaches are 2D electrophoresis (2DE) and subsequent MS, liquid chromatography-MS (LC-MS), and GeLC-MS. Beyond protein identification, there are a number of well-established options available for protein quantification. Difference gel electrophoresis (DIGE) following 2DE is one option but MS-based methods (most commonly iTRAQ-Isobaric Tags for Relative and Absolute Quantification or SILAC-Stable Isotope Labeling by Amino Acids) are now the preferred options. Sample preparation is critical to performing good experiments and subcellular fractionation can additionally provide protein localization information compared with whole cell lysates. Differential detergent solubilization is another valid option. With biological fluids, it is possible to remove the most abundant proteins by immunodepletion. Sample enrichment is also used extensively in certain analyses and most commonly in phosphoproteomics with the initial purification of phosphopeptides. Proteomics produces considerable datasets and resources to facilitate the necessary extended analysis of this data are improving all the time. Beyond the opportunities afforded by proteomics there are definite challenges to achieving full proteomic coverage. Proteomes are highly complex and identifying and quantifying low abundance proteins is a significant issue. Additionally, the analysis of poorly soluble proteins, such as membrane proteins and multiprotein complexes, is difficult. However, it is without doubt that proteomics has already provided significant insights into biological function and this will continue as the technology continues to improve. We also anticipate that the promise of proteomics in terms of biomarker discovery will increasingly be realized.

Quantification of endogenous retinoids

Numerous physiological processes require retinoids, including development, nervous system function, immune responsiveness, proliferation, differentiation, and all aspects of reproduction. Reliable retinoid quantification requires suitable handling and, in some cases, resolution of geometric isomers that have different biological activities. Here we describe procedures for reliable and accurate quantification of retinoids, including detailed descriptions for handling retinoids, preparing standard solutions, collecting samples and harvesting tissues, extracting samples, resolving isomers, and detecting with high sensitivity. Sample-specific strategies are provided for optimizing quantification. Approaches to evaluate assay performance also are provided. Retinoid assays described here for mice also are applicable to other organisms including zebrafish, rat, rabbit, and human and for cells in culture. Retinoid quantification, especially that of retinoic acid, should provide insight into many diseases, including Alzheimer's disease, type 2 diabetes, obesity, and cancer.

Approaches and applications of quantitative LC-MS for proteomics and activitomics

LC-MS is a powerful technique in biomolecular research. In addition to its uses as a tool for protein and peptide quantization, LC-MS can also be used to quantify the activity of signalling and metabolic pathways in a multiplex and comprehensive manner, i.e. as an 'activitomic' tool. Taking cancer research as an illustrative example of application, this review discusses the concepts of biochemical pathway analysis using LC-MS-based proteomic and activitomic techniques.

Quantitation in mass-spectrometry-based proteomics

Mass-spectrometry-based proteomics, the large-scale analysis of proteins by mass spectrometry, has emerged as a new technology over the last decade and become routine in many plant biology laboratories. While early work consisted merely of listing proteins identified in a given organ or under different conditions of interest, there is a growing need to apply comparative and quantitative proteomics strategies toward gaining novel insights into functional aspects of plant proteins and their dynamics. However, during the transition from qualitative to quantitative protein analysis, the potential and challenges will be tightly coupled. Several strategies for differential proteomics that involve stable isotopes or label-free comparisons and their statistical assessment are possible, each having specific strengths and limitations. Furthermore, incomplete proteome coverage and restricted dynamic range still impose the strongest limitations to data throughput and precise quantitative analysis. This review gives an overview of the current state of the art in differential proteomics and possible strategies in data processing.

Organelle proteomics by label-free and SILAC-based protein correlation profiling

The ability to purify cell organelles and protein complexes on a large scale, combined with advances in protein identification using mass spectrometry, has provided a wealth of information regarding protein localization and function. A major challenge in these studies has been the ability to identify bona fide organelle components from a background of co-purifying contaminants because none of the available biochemical purification protocols afford pure preparations. Since this situation is unlikely to change alternative strategies have been devised to meet this challenge by making use of the information inherent in the fractionation profile of organelles isolated by density gradient centrifugation. In this chapter we describe strategies based on protein correlation profiling and quantitative mass spectrometry to sort out likely candidates. The organelle inventories defined by these methods are suitable to guide future functional experiments.

A quantitative proteomics analysis of subcellular proteome localization and changes induced by DNA damage

A major challenge in cell biology is to identify the subcellular distribution of proteins within cells and to characterize how protein localization changes under different cell growth conditions and in response to stress and other external signals. Protein localization is usually determined either by microscopy or by using cell fractionation combined with protein blotting techniques. Both these approaches are intrinsically low throughput and limited to the analysis of known components. Here we use mass spectrometry-based proteomics to provide an unbiased, quantitative, and high throughput approach for measuring the subcellular distribution of the proteome, termed “spatial proteomics.” The spatial proteomics method analyzes a whole cell extract created by recombining differentially labeled subcellular fractions derived from cells in which proteins have been mass-labeled with heavy isotopes. This was used here to measure the relative distribution between cytoplasm, nucleus, and nucleolus of over 2,000 proteins in HCT116 cells. The data show that, at steady state, the proteome is predominantly partitioned into specific subcellular locations with only a minor subset of proteins equally distributed between two or more compartments. Spatial proteomics also facilitates a proteome-wide comparison of changes in protein localization in response to a wide range of physiological and experimental perturbations, shown here by characterizing dynamic changes in protein localization elicited during the cellular response to DNA damage following treatment of HCT116 cells with etoposide. DNA damage was found to cause dissociation of the proteasome from inhibitory proteins and assembly chaperones in the cytoplasm and relocation to associate with proteasome activators in the nucleus.

Proteomics of Saccharomyces cerevisiae Organelles

Knowledge of the subcellular localization of proteins is indispensable to understand their physiological roles. In the past decade, 18 studies have been performed to analyze the protein content of isolated organelles from Saccharomyces cerevisiae. Here, we integrate the data sets and compare them with other large scale studies on protein localization and abundance. We evaluate the completeness and reliability of the organelle proteomics studies. Reliability depends on the purity of the organelle preparations, which unavoidably contain (small) amounts of contaminants from different locations. Quantitative proteomics methods can be used to distinguish between true organellar constituents and contaminants. Completeness is compromised when loosely or dynamically associated proteins are lost during organelle preparation and also depends on the sensitivity of the analytical methods for protein detection. There is a clear trend in the data from the 18 organelle proteomics studies showing that proteins of low abundance frequently escape detection. Proteins with unknown function or cellular abundance are also infrequently detected, indicating that these proteins may not be expressed under the conditions used. We discuss that the yeast organelle proteomics studies provide powerful lead data for further detailed studies and that methodological advances in organelle preparation and in protein detection may help to improve the completeness and reliability of the data.

Application of proteomic marker ensembles to subcellular organelle identification

Compartmentalization of biological processes and the associated cellular components is crucial for cell function. Typically, the location of a component is revealed through a co-localization and/or co-purification with an organelle marker. Therefore, the identification of reliable markers is critical for a thorough understanding of cellular function and dysfunction. We fractionated macrophage-like RAW264.7 cells, both in the resting and endotoxin-activated states, into six fractions representing the major organelles/compartments: nuclei, mitochondria, cytoplasm, endoplasmic reticulum, and plasma membrane as well as an additional dense microsomal fraction. The identity of the first five of these fractions was confirmed via the distribution of conventional enzymatic markers. Through a quantitative liquid chromatography/mass spectrometry-based proteomics analysis of the fractions, we identified 50-member ensembles of marker proteins ("marker ensembles") specific for each of the corresponding organelles/compartments. Our analysis attributed 206 of the 250 marker proteins ( approximately 82%) to organelles that are consistent with the location annotations in the public domain (obtained using DAVID 2008, EntrezGene, Swiss-Prot, and references therein). Moreover, we were able to correct locations for a subset of the remaining proteins, thus proving the superior power of analysis using multiple organelles as compared with an analysis using one specific organelle. The marker ensembles were used to calculate the organelle composition of the six above mentioned subcellular fractions. Knowledge of the precise composition of these fractions can be used to calculate the levels of metabolites in the pure organelles. As a proof of principle, we applied these calculations to known mitochondria-specific lipids (cardiolipins and ubiquinones) and demonstrated their exclusive mitochondrial location. We speculate that the organelle-specific protein ensembles may be used to systematically redefine originally morphologically defined organelles as biochemical entities.

Sperm surface proteomics: from protein lists to biological function

Proteomics technologies have matured significantly in recent years and proteomics driven research articles in reproductive biology and medicine are increasingly common. The key challenge is to move from lists of identified proteins to informed understanding of biological function. This review introduces the range of proteomics workflows most commonly used for protein identification before focusing on the mammalian sperm cell at fertilization as an exemplar for proteomic studies. We review the work of others on entire cells but then argue that proper subcellular fractionation and proper solubilization strategies offers critical advantages to achieving increased biological understanding. In relation to understanding initial gamete recognition events at fertilization (capacitation, zona binding and acrosomal exocytosis) it is imperative to study the sperm surface proteome by using purified plasma membrane fractions. Although this task is challenging there are now strategies at our disposal to achieve comprehensive coverage of the proteins at the sperm surface. Within this context it is also important to understand the milieu of the sperm cell during transit from the testis to the oviduct as proteins (or other entities) from the genital tract epithelia and fluids may also affect the composition and organization of proteins on the sperm surface. Finally the arguments presented for studying the cell plasma membrane proteome to understand the role of the cell surface equally apply to all cell types with important roles in reproductive function.

Combination of several bioinformatics approaches for the identification of new putative glycosyltransferases in Arabidopsis

Approximately 450 glycosyltransferase (GT) sequences have been already identified in the Arabidopsis genome that organize into 40 sequence-based families, but a vast majority of these gene products remain biochemically uncharacterized open reading frames. Given the complexity of the cell wall carbohydrate network, it can be inferred that some of the biosynthetic genes have not yet been identified by classical bioinformatics approaches. With the objective to identify new plant GT genes, we designed a bioinformatic strategy that is based on the use of several remote homology detection methods that act at the 1D, 2D, and 3D level. Together, these methods led to the identification of more than 150 candidate protein sequences. Among them, 20 are considered as putative glycosyltransferases that should further be investigated since known GT signatures were clearly identified.

The organelle proteome of the DT40 lymphocyte cell line

A major challenge in eukaryotic cell biology is to understand the roles of individual proteins and the subcellular compartments in which they reside. Here, we use the localization of organelle proteins by isotope tagging technique to complete the first proteomic analysis of the major organelles of the DT40 lymphocyte cell line. This cell line is emerging as an important research tool because of the ease with which gene knockouts can be generated. We identify 1090 proteins through the analysis of preparations enriched for integral membrane or soluble and peripherally associated proteins and localize 223 proteins to the endoplasmic reticulum, Golgi, lysosome, mitochondrion, or plasma membrane by matching their density gradient distributions to those of known organelle residents. A striking finding is that within the secretory and endocytic pathway a high proportion of proteins are not uniquely localized to a single organelle, emphasizing the dynamic steady-state nature of intracellular compartments in eukaryotic cells.

Isolation of subcellular organelles and structures

One of the major challenges in functional proteomics is the separation of complex protein mixtures to allow detection of low abundance proteins and provide for reliable quantitative and qualitative analysis of proteins impacted by environmental parameters. Prerequisites for the success of such analyses are standardized and reproducible operating procedures for sample preparation prior to protein separation. Due to the complexity of total proteomes, especially of eukaryotic proteomes, and the divergence of protein properties, it is often beneficial to prepare standardized partial proteomes of a given organism to maximize the coverage of the proteome and to increase the chance to visualize low abundance proteins and make them accessible for subsequent analysis. In this chapter we will describe with detailed recipes procedures for the enrichment and isolation of the currently most investigated organelles and subcellular compartments in mammalian cells using classical centrifugation techniques to more sophisticated immunoaffinity-based procedures.

Advancements in plant proteomics using quantitative mass spectrometry

Due to innovative advancements in quantitative MS technologies, proteomics has evolved from taking mere "snapshots" of distinct proteomes in a defined state to monitoring, for instance, changes in abundance, location and/or posttranslational modification(s) of proteins under various conditions, thereby facilitating the functional characterization of proteins in large scale experiments. In plant biology, MS-based quantitative proteomics strategies utilizing stable isotope labeling or label-free methods for protein quantification have only recently been started to find increasing application to comparative and functional proteomics analyses. This review summarizes latest trends and applications in MS-based quantitative plant proteomics and provides insight into different technologies available. In addition, the studies presented here illustrate the enormous potential of quantitative MS for the analysis of important functional aspects with the emphasis on organellar and phosphoproteomics as well as dynamics and turnover of proteins in plants.

Organellar proteomics to create the cell map

The elucidation of a complete, accurate, and permanent representation of the proteome of the mammalian cell may be achievable piecemeal by an organellar based approach. The small volume of organelles assures high protein concentrations. Providing isolated organelles are homogenous, this assures reliable protein characterization within the sensitivity and dynamic range limits of current mass spec based analysis. The stochastic aspect of peptide selection by tandem mass spectrometry for sequence determination by fragmentation is dealt with by multiple biological replicates as well as by prior protein separation on 1-D gels. Applications of this methodology to isolated synaptic vesicles, clathrin coated vesicles, endosomes, phagosomes, endoplasmic reticulum, and Golgi apparatus, as well as Golgi-derived COPI vesicles, have led to mechanistic insight into the identity and function of these organelles.