Comparison of Three Commercially Available DIGE Analysis Software Packages: Minimal User Intervention in Gel-Based Proteomics

DIGE Analysis Software and Protein Identification Approaches

Two-dimensional difference gel electrophoresis (2D-DIGE) is a high-resolution protein separation technique, with the excellent dynamic range obtained by fluorescent tag labeling of protein samples. Scanned images of 2D-DIGE gels show thousands of protein spots, each spot representing a single or a group of protein isoforms. By using commercially available software, each protein spot is defined by an outline, which is digitized and correlated with the quantity of proteins present in each spot. Software packages include DeCyder, SameSpots, and Dymension 3. In addition, proteins of interest can be excised from post-stained gels and identified with conventional mass spectrometric techniques. High-throughput mass spectrometry is performed using sophisticated instrumentation, including matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF), MALDI-TOF/TOF, and liquid chromatography tandem mass spectrometry (LC-MS/MS). Tandem MS (MALDI-TOF/TOF or LC-MS/MS) analyzes fragmented peptides, resulting in amino acid sequence information, which is especially useful when protein spots are low abundant or where a mixture of proteins is present.

Application of Two-Dimensional Difference Gel Electrophoresis in Identification of Factors Responsible for Virulence of Staphylococcus aureus

Staphylococcus aureus is a dangerous opportunistic pathogen of humans and animals. Highly virulent and multi-antibiotic-resistant strains are of particular concern due to high invasiveness and limited array of useful treatment options. Proteomics allows identification and investigation of staphylococcal virulence factors to better understand and treat the related disease. Two-dimensional difference gel electrophoresis (2D DIGE) is a powerful method for identification of differences in staphylococcal proteomes, both intracellular and secretory. Not only the presence of particular proteins and their quantities may be determined, but also each modification changing the molecular mass and/or isoelectric point of a protein is trackable. Especially, 2D DIGE allows for detection of posttranslational modifications, including processing and degradation by proteases. For differential analysis, protein samples are labeled with spectrally distinguishable fluorescent dyes, mixed and separated according to their isoelectric point (first dimension), and then electrophoresed in the presence of sodium dodecyl sulfate according to their molecular mass (second dimension). Exceptional resolution of 2D DIGE allows to obtain focused and sharp protein spots, and identify a large number of differentiating proteins. Here we provide protocols for TRI Reagent-based preparation of high-quality samples for 2D DIGE, sample separation, and ways of handling differentiating protein spots which lead to samples ready for protein identification using MS.

Quantitative proteomic strategies to study reproduction in farm animals: Female reproductive fluids

Reproductive fluids from the female reproductive tract are gaining attention for their potential to support and optimize reproductive processes, including gamete maturation and embryo culture in vitro. Quantitative proteomics is a powerful way to decipher the proteome of reproductive tract fluids and to identify biologically relevant proteins. The present review describes proteomic strategies for analysing female reproductive fluid proteins. In addition, it considers the strategies for the preparation of oviductal, uterine and follicular fluid samples. Finally, it highlights the main results of quantitative proteomic studies, providing insights into the biological processes related to reproductive biology in farm animals. SIGNIFICANCE: Assisted reproductive technologies (ARTs) have become vitally important for farm animal breeding and much effort is going into the optimization and refinement of the techniques. There are also attempts to imitate physiological conditions by adding reproductive fluids or individual fluid proteins to improve in vitro procedures. A detailed knowledge of the reproductive fluid proteomes is indispensable. The present review summarizes the most widely used quantitative proteomic approaches for the analysis of fluids from the female reproductive tract and highlights the potential of quantitative proteomics to delineate reproductive processes and identify candidate proteins for ARTs in farm animals.

2D-DIGE and Fluorescence Image Analysis

2D-DIGE is still a very widespread technique in proteomics for the identification of panels of biomarkers, allowing to tackle with some important drawback of classical two-dimensional gel-electrophoresis. However, once 2D-gels are obtained, they must undergo a quite articulated multistep image analysis procedure before the final differential analysis via statistical mono- and multivariate methods. Here, the main steps of image analysis software are described and the most recent procedures reported in the literature are briefly presented.

Use of liquid isoelectric focusing (OFFGEL) on the discovery of meat tenderness biomarkers

Protein biomarkers of meat tenderness are known to be of primary importance for the prediction of meat quality, and hence, industry profitability. Proteome analysis was performed on meat from 8 Main Anjou beef cattle, previously classified as tender or tough meats by Warner Bratzler shear force measurements. Myofibrillar fraction of Longissimus thoracis muscle was separated by a novel fractionation approach based on liquid isoelectric focusing (OFFGEL) and further analyzed by SDS-PAGE and liquid chromatography coupled to tandem mass spectrometry. Obtained OFFGEL fraction profiles were reproducible allowing the comparison of both meat qualities and revealing 7 protein bands capable to discriminate between tender and tough samples. The proteins present in these bands were troponin T, Heat Shock protein beta-1, creatine kinase, actin, troponin C, myosins 1 and 2 and myozenin-1. The latter protein has not been previously reported as a marker of meat tenderness.

SIGNIFICANCE

This study introduces an innovative proteomic approach for the study of muscle proteome. The fact of obtaining fractions in liquid state after OFFGEL fractionation allows for a faster analysis of proteins by mass spectrometry, being an interesting alternative to more classical proteomic approaches based on two dimensional gel electrophoresis (2-DE).

DIGE Analysis Software and Protein Identification Approaches

DIGE is a high-resolution two-dimensional gel electrophoresis method, with excellent dynamic range obtained by fluorescent tag labeling of protein samples. Scanned images of DIGE gels show thousands of protein spots, each spot representing a single or a group of protein isoforms. By using commercially available software, each protein spot is defined by an outline, which is digitized and correlated with the quantity of proteins present in each spot. Software packages include DeCyder, SameSpots, and Dymension 3. In addition, proteins of interest can be excised from post-stained gels and identified with conventional mass spectrometry techniques. High-throughput mass spectrometry is performed using sophisticated instrumentation including matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF), MALDI-TOF/TOF, and liquid chromatography tandem mass spectrometry (LC-MS/MS). Tandem MS (MALDI-TOF/TOF or LC-MS/MS), analyzes fragmented peptides, resulting in amino acid sequence information, especially useful when protein spots are low abundant or where a mixture of proteins is present.

The impact of growth hormone on proteomic profiles: a review of mouse and adult human studies

Growth hormone (GH) is a protein that is known to stimulate postnatal growth, counter regulate insulin's action and induce expression of insulin-like growth factor-1. GH exerts anabolic or catabolic effects depending upon on the targeted tissue. For instance, GH increases skeletal muscle and decreases adipose tissue mass. Our laboratory has spent the past two decades studying these effects, including the effects of GH excess and depletion, on the proteome of several mouse and human tissues. This review first discusses proteomic techniques that are commonly used for these types of studies. We then examine the proteomic differences found in mice with excess circulating GH (bGH mice) or mice with disruption of the GH receptor gene (GHR^-/-). We also describe the effects of increased and decreased GH action on the proteome of adult patients with either acromegaly, GH deficiency or patients after short-term GH treatment. Finally, we explain how these proteomic studies resulted in the discovery of potential biomarkers for GH action, particularly those related with the effects of GH on aging, glucose metabolism and body composition.

GENOCOP Algorithm and Hierarchical Grid Transformation for Image Warping of Two-Dimensional Gel Electrophoretic Maps

Hierarchical grid transformation is a powerful hierarchical approach to 2-D map warping, able to model both global and local deformations. The algorithm can be stopped when a desired degree of accuracy in the images alignment is obtained. The deformed image is warped and aligned to the target image using a grid where the number of nodes increases in each step of the algorithm. The numerical optimization of the position of the nodes of the grid can be efficiently solved by genetic algorithms, ensuring the achievement of the optimal position of the nodes with a low computational cost with respect to other methods. Here, the optimization of the position of the nodes is carried out by GENOCOP (genetic algorithm for numerical optimization of constrained problems), refined by the following conjugate gradient optimization step. The modeling of the warped space is then achieved by a spline model where some constraints are introduced in the choice of the nodes that are moved. The whole procedure can be intended as an evolutionary method that models the deformation of the gel map at different levels of detail.

Revealing oxidative damage to enzymes of carbohydrate metabolism in yeast: An integration of 2D DIGE, quantitative proteomics, and bioinformatics

Clinical usage of lidocaine, a pro-oxidant has been linked with severe, mostly neurological complications. The mechanism(s) causing these complications is independent of the blockade of voltage-gated sodium channels. The budding yeast Saccharomyces cerevisiae lacks voltage-gated sodium channels, thus provides an ideal system to investigate lidocaine-induced protein and pathway alterations. Whole-proteome alterations leading to these complications have not been identified. To address this, S. cerevisiae was grown to stationary phase and exposed to an LC50 dose of lidocaine. The differential proteomes of lidocaine treatment and control were resolved 6 h post exposure using 2D DIGE. Amine reactive dyes and carbonyl reactive dyes were used to assess protein abundance and protein oxidation, respectively. Quantitative analysis of these dyes (⩾ 1.5-fold alteration, p ⩽ 0.05) revealed a total of 33 proteoforms identified by MS differing in abundance and/or oxidation upon lidocaine exposure. Network analysis showed enrichment of apoptotic proteins and cell wall maintenance proteins, while the abundance of proteins central to carbohydrate metabolism, such as triosephosphate isomerase and glyceraldehyde-3-phosphate dehydrogenase, and redox proteins superoxide dismutase and peroxiredoxin were significantly decreased. Enzymes of carbohydrate metabolism, such as phosphoglycerate kinase and enolase, the TCA cycle enzyme aconitase, and multiple ATP synthase subunits were found to be oxidatively modified. Also, the activity of aconitase was found to be decreased. Overall, these data suggest that toxic doses of lidocaine induce significant disruption of glycolytic pathways, energy production, and redox balance, potentially leading to cell malfunction and death.

Comparative Evaluation of Software Features and Performances

Analysis of two-dimensional gel images is a crucial step for the determination of changes in the protein expression, but at present, it still represents one of the bottlenecks in 2-DE studies. Over the years, different commercial and academic software packages have been developed for the analysis of 2-DE images. Each of these shows different advantageous characteristics in terms of quality of analysis. In this chapter, the characteristics of the different commercial software packages are compared in order to evaluate their main features and performances.

Three-dimensional electrophoresis for quantitative profiling of complex proteomes

Quantitative 2D-gel-dependent proteomics became feasible with 2D fluorescence difference gel electrophoresis (2D-DIGE), and this technique has gained wide acceptance because it has eliminated the gel to gel variations and greatly facilitated the quantitative comparisons across gels for many different experimental conditions. However, the co-migration of several proteins in the same spot is still a major limitation which detracts from the accuracy of comparative quantification and prevents unambiguous post-translational modifications (PTMs) detection.A protocol based on traditional polyacrylamide gel IEF sample fractionation, and followed by two consecutive SDS-PAGE electrophoreses alleviates co-migration limitations. The use of two different buffer systems for SDS-PAGE is central to the proposed approach.

Comparative proteomic analysis of ovary for Chinese rare minnow (Gobiocypris rarus) exposed to chlorophenol chemicals

Pentachlorophenol (PCP) and 2,4,6-trichlorophenol (TCP) are suspected of disrupting the endocrine system and thus affecting human and wildlife reproduction, but the potential common mechanisms and biomarkers of chlorophenols (CPs) in the ovary are not fully elucidated. In the present study, the female rare minnow (Gobiocypris rarus) was exposed to PCP (0.5, 5.0, and 50 μg/L), TCP (1.0, 10, and 100 μg/L) and 17β-estradiol (as a positive control) for 28 days, and the matrix-assisted laser desorption/ionization (MALDI) tandem time-of-flight (TOF/TOF) mass spectrometry analysis was employed to investigate the alteration of protein expression in the ovary. After comparison of the protein profiles from treated and control groups, 22 protein spots were observed to be altered in abundance (>2-fold) from female treated groups, and 14 protein spots were identified successfully. These proteins were related to molecular response patterns, endocrine effects, metabolic pathways, and even the possible carcinogens in response to CP exposure. The seven differentially expressed mRNA encoding proteins were measured by quantitative real-time PCR (QRT-PCR) and histopathology was also measured. Our data demonstrate that alterations of multiple pathways may be associated with the toxic effects of CPs on ovaries.

BIOLOGICAL SIGNIFICANCE

Although numerous studies have shown the affection of the endocrine system with exposure to chlorophenols (CPs), there is little report on the alterations of protein expression in the ovaries from rare minnows following exposure to PCP or TCP. In the present study, a comparative proteomic approach using two dimensional gel electrophoresis and mass spectrometry (MALDI-TOF/TOF MS) has been developed to identify certain proteins in the ovaries of Chinese rare minnow, whose abundance changes during exposure to CPs. After comparison of the protein profiles from treated and control groups, 22 protein spots were observed to be altered in abundance (>2-fold) from female treated groups, and 14 protein spots were identified successfully. These proteins were related to molecular response patterns, endocrine effects, metabolic pathways, and even the possible carcinogens in response to CP exposure. Because the mechanism often involves changes in the expression of multiple proteins rather than a single protein, a global analysis of the protein alterations can result in valuable information to understand the CP action mechanism. All the above results demonstrate that the Vtg, SUMO, Lec-3 and PIMT protein are potential biomarkers and involved in the toxicity pathway of CP exposure in aquatic animals, which should be the primary focus of studies on the CP ovary toxicity mechanism in the future.

High dynamic range proteome imaging with the structured illumination gel imager

A current challenge for proteomics is detecting proteins over the large concentration ranges found in complex biological samples such as whole-cell extracts. Currently, no unbiased, whole-proteome analysis scheme is capable of detecting the full range of cellular proteins. This is due in part to the limited dynamic range of the detectors used to sense proteins or peptides. We present a new technology, structured illumination (SI) gel imager, which detects fluorescently labeled proteins in electrophoretic gels over a 1 000 000-fold concentration range. SI uses computer-generated masks to attenuate the illumination of highly abundant proteins, allowing for long exposures of low-abundance proteins, thus avoiding detector saturation. A series of progressively masked gel images are assembled into a single, very high dynamic range image. We demonstrate that the SI imager can detect proteins over a concentration range of approximately 1 000 000-fold, making it a useful tool for comprehensive, unbiased proteome-wide surveys.

Proteomic profiling of the dystrophin-deficient mdx phenocopy of dystrophinopathy-associated cardiomyopathy

Cardiorespiratory complications are frequent symptoms of Duchenne muscular dystrophy, a neuromuscular disorder caused by primary abnormalities in the dystrophin gene. Loss of cardiac dystrophin initially leads to changes in dystrophin-associated glycoproteins and subsequently triggers secondarily sarcolemmal disintegration, fibre necrosis, fibrosis, fatty tissue replacement, and interstitial inflammation. This results in progressive cardiac disease, which is the cause of death in a considerable number of patients afflicted with X-linked muscular dystrophy. In order to better define the molecular pathogenesis of this type of cardiomyopathy, several studies have applied mass spectrometry-based proteomics to determine proteome-wide alterations in dystrophinopathy-associated cardiomyopathy. Proteomic studies included both gel-based and label-free mass spectrometric surveys of dystrophin-deficient heart muscle from the established mdx animal model of dystrophinopathy. Comparative cardiac proteomics revealed novel changes in proteins associated with mitochondrial energy metabolism, glycolysis, signaling, iron binding, antibody response, fibre contraction, basal lamina stabilisation, and cytoskeletal organisation. This review summarizes the importance of studying cardiomyopathy within the field of muscular dystrophy research, outlines key features of the mdx heart and its suitability as a model system for studying cardiac pathogenesis, and discusses the impact of recent proteomic findings for exploring molecular and cellular aspects of cardiac abnormalities in inherited muscular dystrophies.

Protein profiling using two-dimensional difference gel electrophoresis (2-D DIGE)

2-D DIGE relies on pre-electrophoretic labeling of samples with one of three spectrally distinct fluorescent dyes, followed by electrophoresis of all samples in one 2-D gel. The dye-labeled samples are then viewed individually by scanning the gel at different wavelengths, which circumvents problems with gel-to-gel variation and spot matching between gels. Image analysis programs are used to generate volume ratios for each spot, which essentially describe the intensity of a particular spot in each test sample, and thus enable protein abundance level changes to be identified and quantified. This unit describes the 2-D DIGE procedure including sample preparation from various cell types, labeling of proteins, and points to consider in the downstream processing of fluorescently labeled samples.

Application of fluorescence two-dimensional difference in-gel electrophoresis as a proteomic biomarker discovery tool in muscular dystrophy research

In this article, we illustrate the application of difference in-gel electrophoresis for the proteomic analysis of dystrophic skeletal muscle. The mdx diaphragm was used as a tissue model of dystrophinopathy. Two-dimensional gel electrophoresis is a widely employed protein separation method in proteomic investigations. Although two-dimensional gels usually underestimate the cellular presence of very high molecular mass proteins, integral membrane proteins and low copy number proteins, this method is extremely powerful in the comprehensive analysis of contractile proteins, metabolic enzymes, structural proteins and molecular chaperones. This gives rise to two-dimensional gel electrophoretic separation as the method of choice for studying contractile tissues in health and disease. For comparative studies, fluorescence difference in-gel electrophoresis has been shown to provide an excellent biomarker discovery tool. Since aged diaphragm fibres from the mdx mouse model of Duchenne muscular dystrophy closely resemble the human pathology, we have carried out a mass spectrometry-based comparison of the naturally aged diaphragm versus the senescent dystrophic diaphragm. The proteomic comparison of wild type versus mdx diaphragm resulted in the identification of 84 altered protein species. Novel molecular insights into dystrophic changes suggest increased cellular stress, impaired calcium buffering, cytostructural alterations and disturbances of mitochondrial metabolism in dystrophin-deficient muscle tissue.

Proteomics applied to transfusion plasma: the beginning of the story

'Safe blood' is and has always been the major concern in transfusion medicine. Plasma can undergo virus inactivation treatments based on physicochemical, photochemical or thermal methodologies for pathogen inactivation. The validation of these treatments is essentially based on clottability assays and clotting factors' titration; however, their impact on plasma proteins at the molecular level has not yet been evaluated. Proteomics appears as particularly adapted to identify, to localize and, consequently, to correlate these modifications to the biological activity change. At the crossroads of biology and analytical sciences, proteomics is the large-scale study of proteins in tissues, physiological fluids or cells at a given moment and in a precise environment. The proteomic strategy is based on a set of methodologies involving separative techniques like mono- and bidimensional gel electrophoresis and chromatography, analytical techniques, especially mass spectrometry, and bioinformatics. Even if plasma has been extensively studied since the very beginning of proteomics, its application to transfusion medicine has just begun. In the first part of this review, we present the principles of proteomics analysis. Then, we propose a state of the art of proteomics applied to plasma analysis. Finally, the use of proteomics for the evaluation of the impact of storage conditions and pathogen inactivation treatments applied to transfusion plasma and for the evaluation of therapeutic protein fractionated is discussed.

Comparative proteomics of inner membrane fraction from carbapenem-resistant Acinetobacter baumannii with a reference strain

Acinetobacter baumannii has been identified by the Infectious Diseases Society of America as one of the six pathogens that cause majority of hospital infections. Increased resistance of A.baumannii even to the latest generation of β-lactams like carbapenem is an immediate threat to mankind. As inner-membrane fraction plays a significant role in survival of A.baumannii, we investigated the inner-membrane fraction proteome of carbapenem-resistant strain of A.baumannii using Differential In-Gel Electrophoresis (DIGE) followed by DeCyder, Progenesis and LC-MS/MS analysis. We identified 19 over-expressed and 4 down-regulated proteins (fold change>2, p<0.05) in resistant strain as compared to reference strain. Some of the upregulated proteins in resistant strain and their association with carbapenem resistance in A.baumannii are: i) β-lactamases, AmpC and OXA-51: cleave and inactivate carbapenem ii) metabolic enzymes, ATP synthase, malate dehydrogenase and 2-oxoglutarate dehydrogenase: help in increased energy production for the survival and iii) elongation factor Tu and ribosomal proteins: help in the overall protein production. Further, entry of carbapenem perhaps is limited by controlled production of OmpW and low levels of surface antigen help to evade host defence mechanism in developing resistance in A.baumannii. Present results support a model for the importance of proteins of inner-membrane fraction and their synergistic effect in the mediation of resistance of A.baumannii to carbapenem.

GENOCOP algorithm and hierarchical grid transformation for image warping of two dimensional gel eletrophoretic maps

Hierarchical grid transformation is a powerful approach to SDS 2DPAGE maps warping. The hierarchy of the warping transformation is able to model both global and local deformations of the gels and the algorithm can be stopped when a certain degree of accuracy in the image alignment is obtained. The numerical optimization of the position of the nodes of the grid that are responsible for the image warping is a multivariate task that can be solved efficiently using Genetic Algorithms. The use of Genetic Algorithms ensures that an optimal position of the nodes can be defined with a low computational cost with respect to other methods. The optimal positions of the nodes of the grid can be successfully used for defining a good warping of the gels.

Enabling technologies for yeast proteome analysis

Whilst the study of yeast genomes and transcriptomes is in an advanced state, there is still much to learn about the resulting proteins in terms of cataloging, characterization of post-translational modifications, turnover, and the dynamics of sub-cellular localization and interactions. Analysis of the transcripts gives little insight into function or diversity as changes in RNA levels do not always correlate with the resulting protein abundance. A number of global and targeted attempts have been made to catalog and characterize the yeast proteome and we describe here the methods used to gain a greater understanding of the yeast proteome. This comprehensive review also describes future approaches that will aid completion in identifying and characterizing the remaining 20% of the undetermined yeast proteome as well as giving new insight into protein dynamics.

Image Analysis Workflow for 2-D Electrophoresis Gels Based on ImageJ

A number of commercial software packages are currently available to perform digital two-dimensional electrophoresis (2D-GE) gel analysis. However, both the high cost of the commercial packages and the unavailability of a standard data analysis workflow, have prompted several groups to develop freeware systems to perform certain steps of gel analysis. Unfortunately, to the best of our knowledge none of them offer a package that performs all the steps envisaged in a 2D-GE gel analysis. Here we describe an ImageJ-based procedure, able to manage all the steps of a 2D-GE gel analysis. ImageJ is a free available image processing and analysis application developed by National Institutes of Health (NIH) and widely used in different life sciences fields as medical imaging, microscopy, western blotting and PAGE. Nevertheless no one has yet developed a procedure enabled to compare spots on 2D-GE gels. We collected all used ImageJ tools in a plug-in that allows us to perform the whole 2D-GE analysis. To test it, we performed a set of 2D-GE experiments on plasma samples from 9 patients victims of acute myocardial infarction and 8 controls, and we compared the results obtained by our procedure to those obtained using a widely diffuse commercial package, finding similar performances.

Glycomic and glycoproteomic analysis of serum from patients with stomach cancer reveals potential markers arising from host defense response mechanisms

Despite the reduced incidence of gastric cancer in the developed world, a diagnosis of stomach carcinoma still carries a poor prognosis due to the asymptomatic nature of the disease in the early stages, subsequent advanced stage diagnosis, and a low 5 year survival rate. Endoscopy remains the primary standard for diagnosis of stomach carcinoma and the current marker, carbohydrate antigen 19-9 (CA19-9) lacks the levels of sensitivity and specificity required in order to make it clinically useful for diagnostic monitoring. Therefore, there is a current need for additional markers to improve the diagnostic accuracy for the early stages of stomach cancer. Together, glycomic, proteomic, and glycoproteomic analyses of serum have the potential to identify such probable markers. A discovery study is reported here using preoperative serum from 80 stomach cancer patients, 10 patients bearing benign stomach disease, and 20 matched controls. Glycomic analysis of the total and immunoaffinity depleted serum revealed statistically significant increases in the levels of sialyl Lewis X epitopes (SLe(X)) present on triantennary glycans accompanied by increased levels of core fucosylated agalactosyl biantennary glycans present on IgG (referred to as the IgG G0 glycoform) which are associated with increasing disease pathogenesis. Protein expression analysis using 2D-DiGE returned a number of differentially expressed protein candidates in the depleted serum, many of which were shown to carry triantennary SLe(X) during subsequent glycomic investigations. Biological pathway analysis of the experimental data returned complement activation and acute phase response signaling as the most significantly altered pathways in the stomach cancer patient serum. Upon the basis of these findings, it is suggested that increased expression of IgG G0 and complement activation are a host response to the presence of the stomach tumor while the increased expression of SLe(X) and acute phase response proteins is a result of pro-inflammatory cytokine signaling, including IL-6, during carcinogenesis. The approach presented herein provides an insight into the underlying mechanisms of disease and the resulting changes in the glycome and glycoproteome offer promise as potential markers for diagnosis and prognostic monitoring in stomach cancer.

Image analysis tools and emerging algorithms for expression proteomics

Since their origins in academic endeavours in the 1970s, computational analysis tools have matured into a number of established commercial packages that underpin research in expression proteomics. In this paper we describe the image analysis pipeline for the established 2-DE technique of protein separation, and by first covering signal analysis for MS, we also explain the current image analysis workflow for the emerging high-throughput 'shotgun' proteomics platform of LC coupled to MS (LC/MS). The bioinformatics challenges for both methods are illustrated and compared, whereas existing commercial and academic packages and their workflows are described from both a user's and a technical perspective. Attention is given to the importance of sound statistical treatment of the resultant quantifications in the search for differential expression. Despite wide availability of proteomics software, a number of challenges have yet to be overcome regarding algorithm accuracy, objectivity and automation, generally due to deterministic spot-centric approaches that discard information early in the pipeline, propagating errors. We review recent advances in signal and image analysis algorithms in 2-DE, MS, LC/MS and Imaging MS. Particular attention is given to wavelet techniques, automated image-based alignment and differential analysis in 2-DE, Bayesian peak mixture models, and functional mixed modelling in MS, and group-wise consensus alignment methods for LC/MS.

Feature detection techniques for preprocessing proteomic data

Numerous gel-based and nongel-based technologies are used to detect protein changes potentially associated with disease. The raw data, however, are abundant with technical and structural complexities, making statistical analysis a difficult task. Low-level analysis issues (including normalization, background correction, gel and/or spectral alignment, feature detection, and image registration) are substantial problems that need to be addressed, because any large-level data analyses are contingent on appropriate and statistically sound low-level procedures. Feature detection approaches are particularly interesting due to the increased computational speed associated with subsequent calculations. Such summary data corresponding to image features provide a significant reduction in overall data size and structure while retaining key information. In this paper, we focus on recent advances in feature detection as a tool for preprocessing proteomic data. This work highlights existing and newly developed feature detection algorithms for proteomic datasets, particularly relating to time-of-flight mass spectrometry, and two-dimensional gel electrophoresis. Note, however, that the associated data structures (i.e., spectral data, and images containing spots) used as input for these methods are obtained via all gel-based and nongel-based methods discussed in this manuscript, and thus the discussed methods are likewise applicable.

Highlights on the capacities of "Gel-based" proteomics

Gel-based proteomic is the most popular and versatile method of global protein separation and quantification. This is a mature approach to screen the protein expression at the large scale, and a cheaper approach as compared with gel-free proteomics. Based on two independent biochemical characteristics of proteins, two-dimensional electrophoresis combines isoelectric focusing, which separates proteins according to their isoelectric point, and SDS-PAGE, which separates them further according to their molecular mass. The next typical steps of the flow of gel-based proteomics are spots visualization and evaluation, expression analysis and finally protein identification by mass spectrometry. For the study of differentially expressed proteins, two-dimensional electrophoresis allows simultaneously to detect, quantify and compare up to thousand protein spots isoforms, including post-translational modifications, in the same gel and in a wide range of biological systems. In this review article, the limits, benefits, and perspectives of gel-based proteomic approaches are discussed using concrete examples.