Elsie 4: quantitative computer analysis of sets of two-dimensional gel electrophoretograms

We have developed and refined a system for quantitative computer analysis of two-dimensional polyacrylamide gel electrophoretograms. The system, named Elsie 4, is based on one described by Vo et al. (Anal. Biochem. 112, 258 (1981]. It is highly automated. Elsie 4 can find, and measure the intensity of, almost any spot resolvable on two-dimensional gels, including spots visible only as shoulders off larger spots and spots so close together that there is no "valley" between them. It can automatically match the spot patterns of different gels, potentially without the need for a user to provide landmark matches. The matches between paired gels let us follow the synthesis of any spot through a set of gels. Information about a group of matched spots can be obtained by referring to any spot in the group. There is generally no need for a standard or reference gel. Data for two experiments can be combined and compared by matching any gel in one experiment with any gel in the other. There are ways to automatically find possible mismatches in sets of gels. Scans and the results of the analysis can be shown on an image displayer. The programs use function libraries; this helps ensure consistency and increase portability. The programs and functions can be linked together in many ways; this lets users build custom programs for analysis of specific experiments.     

Comparison of PDQuest and Progenesis software packages in the analysis of two-dimensional electrophoresis gels

Efficient analysis of protein expression by using two-dimensional electrophoresis (2-DE) data relies on the use of automated image processing techniques. The overall success of this research depends critically on the accuracy and the reliability of the analysis software. In addition, the software has a profound effect on the interpretation of the results obtained, and the amount of user intervention demanded during the analysis. The choice of analysis software that best meets specific needs is therefore of interest to the research laboratory. In this paper we compare two advanced analysis software packages, PDQuest and Progenesis. Their evaluation is based on quantitative tests at three different levels of standard 2-DE analysis: spot detection, gel matching and spot quantitation. As test materials we use three gel sets previously used in a similar comparison of Z3 and Melanie, and three sets of gels from our own research. It was observed that the quality of the test gels critically influences the spot detection and gel matching results. Both packages were sensitive to the parameter or filter settings with respect to the tendency of finding true positive and false positive spots. Quantitation results were very accurate for both analysis software packages.     

A proteomics study of in vitro cyst germination and appressoria formation in Phytophthora infestans

A proteomics study using two-dimensional gel electrophoresis (2-DE) and mass spectrometry was performed on Phytophthora infestans. Proteins from cysts, germinated cysts and appressoria grown in vitro were isolated and separated by 2-DE. Statistical quantitative analysis of the protein spots from five independent experiments of each developmental stage revealed significant up-regulation of ten spots on gels from germinated cysts compared to cysts. Five spots were significantly up-regulated on gels from appressoria compared to germinated cysts and one of these up-regulated spots was not detectable on gels from cysts. In addition, one spot was significantly down-regulated and another spot not detectable on the gels from appressoria. The corresponding proteins to 13 of these spots were identified with high confidence using tandem mass spectrometry and database searches. The functions of the proteins that were up-regulated in germinated cysts and appressoria can be grouped into the following categories: protein synthesis (e.g. a DEAD box RNA helicase), amino acid metabolism, energy metabolism and reactive oxygen species scavenging. The spot not detected in appressoria was identified as the P. infestans crinkling- and necrosis-inducing protein CRN2. The identified proteins are most likely involved in the establishment of the infection of the host plant.     

A probabilistic treatment of the missing spot problem in 2D gel electrophoresis experiments

Two-dimensional SDS-PAGE gel electrophoresis using post-run staining is widely used to measure the abundances of thousands of protein spots simultaneously. Usually, the protein abundances of two or more biological groups are compared using biological and technical replicates. After gel separation and staining, the spots are detected, spot volumes are quantified, and spots are matched across gels. There are almost always many missing values in the resulting data set. The missing values arise either because the corresponding proteins have very low abundances (or are absent) or because of experimental errors such as incomplete/over focusing in the first dimension or varying run times in the second dimension as well as faulty spot detection and matching. In this study, we show that the probability for a spot to be missing can be modeled by a logistic regression function of the logarithm of the volume. Furthermore, we present an algorithm that takes a set of gels with technical and biological replicates as input and estimates the average protein abundances in the biological groups from the number of missing spots and measured volumes of the present spots using a maximum likelihood approach. Confidence intervals for abundances and p-values for differential expression between two groups are calculated using bootstrap sampling. The algorithm is compared to two standard approaches, one that discards missing values and one that sets all missing values to zero. We have evaluated this approach in two different gel data sets of different biological origin. An R-program, implementing the algorithm, is freely available at http://bioinfo.thep .lu.se/MissingValues2Dgels.html.     

Comparison of SYPRO Ruby and Flamingo fluorescent stains for application in proteomic research

Fluorescent dyes are widely used for the detection and quantitation of proteins separated by polyacrylamide gel electrophoresis. SYPRO Ruby is one such fluorescent dye widely used for this purpose. More recently, another fluorescent dye, Flamingo, is available for expression proteomic research. Using a standard ultraviolet (UV) transilluminator and a charge-coupled device (CCD)-based imaging system, the relative sensitivity of these two different fluorescent stains with regard to detection of protein spots separated by two-dimensional gel electrophoresis (2D-GE) and identification by liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) were compared. Using mouse kidney and liver homogenates as well as Escherichia coli extract, we detected a greater number of protein spots using Flamingo compared with SYPRO Ruby. In addition, when we compared the number of matched peptides and the percentage of amino acid residues identified for 22 different protein spots of mouse kidney proteome, we observed a higher number of matched peptides and a higher percentage of amino acid residues for the majority of the proteins using Flamingo compared with SYPRO Ruby. Also, we were able to characterize a protein spot that can be detected by Flamingo only. Therefore, we recommend Flamingo over SYPRO Ruby to be used for studies on expression proteomics.     

Improved comparative proteome analysis based on two-dimensional gel electrophoresis

The purpose of this study was to test the extent to which differences in spot intensity can be reliably recognized between two groups of two-dimensional electrophoresis gels (pH 4-7, visualized with ruthenium fluorescent stain) each loaded with different amounts of protein from rat brain (power analysis). Initial experiments yielded only unsatisfactory results: 546 spots were matched from two groups of 6 gels each loaded with 200 microg and 250 microg protein, respectively. Only 72 spots were higher (p<0.05), while 58 spots were significantly lower in the 250-microg group. The construction of new apparatuses that allowed the simultaneous processing of 24 gels throughout all steps between rehydration and staining procedure considerably lowered the between-gel variation. This resulted in the detection of significant differences in spot intensities in 77-90% of all matched spots on gel groups with a 25% difference in protein load. This applied both when protein from 24 biological replicates was loaded onto two groups of 12 gels and when two pooled tissue samples were each loaded onto 6 gels. At a difference of 50% in protein load, more than 90% of all spots differed significantly between two experimental groups.     

Proteomic comparison of two-dimensional gel electrophoresis profiles from human lung squamous carcinoma and normal bronchial epithelial tissues

Differential proteome profiles of human lung squamous carcinoma tissue compared to paired tumor-adjacent normal bronchial epithelial tissue were established and analyzed by means of immobilized pH gradient-based two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) and matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS). The results showed that well-resolved, reproducible 2-DE patterns of human lung squamous carcinoma and adjacent normal bronchial epithelial tissues were obtained under the condition of 0.75-mg protein-load. The average deviation of spot position was 0.733+/-0.101 mm in IEF direction, and 0.925+/-0.207 mm in SDS-PAGE direction. For tumor tissue, a total of 1241+/-88 spots were detected, 987+/-65 spots were matched with an average matching rate of 79.5%. For control, a total of 1190+/-72 spots were detected, and 875+/-48 spots were matched with an average matching rate of 73.5%. A total of 864+/-34 spots were matched between tumors and controls. Forty-three differential proteins were characterized: some proteins were related to oncogenes, and others involved in the regulation of cell cycle and signal transduction. It is suggested that the differential proteomic approach is valuable for mass identification of differentially expressed proteins involved in lung carcinogenesis. These data will be used to establish human lung cancer proteome database to further study human lung squamous carcinoma.     

Protein synthesis in synaptosomes: a proteomics analysis

A proteomics approach was used to identify the translation products of a unique synaptic model system, squid optic lobe synaptosomes. Unlike its vertebrate counterparts, this preparation is largely free of perikaryal cell fragments and consists predominantly of pre-synaptic terminals derived from retinal photoreceptor neurones. We metabolically labelled synaptosomes with [(35)S] methionine and applied two-dimensional gel electrophoresis to resolve newly synthesized proteins at high resolution. Autoradiographs of blotted two-dimensional gels revealed de novo synthesis of about 80 different proteins, 18 of which could be matched to silver-stained gels that were run in parallel. In-gel digestion of the matched spots and mass spectrometric analyses revealed the identities of various cytosolic enzymes, cytoskeletal proteins, molecular chaperones and nuclear-encoded mitochondrial proteins. A number of novel proteins (i.e. not matching with database sequences) were also detected. In situ hybridization was employed to confirm the presence of mRNA and rRNA in synaptosomes. Together, our data show that pre-synaptic endings of squid photoreceptor neurones actively synthesize a wide variety of proteins involved in synaptic functioning, such as transmitter recycling, energy supply and synaptic architecture.     

Proteomic methodological recommendations for studies involving human plasma, platelets, and peripheral blood mononuclear cells

This study was designed to develop, optimize and validate protocols for blood processing prior to proteomic analysis of plasma, platelets and peripheral blood mononuclear cells (PBMC) and to determine analytical variation of a single sample of depleted plasma, platelet and PBMC proteins within and between four laboratories each using their own standard operating protocols for 2D gel electrophoresis. Plasma depleted either using the Beckman Coulter IgY-12 proteome partitioning kit or the Amersham albumin and IgG depletion columns gave good quality gels, but reproducibility appeared better with the single-use immuno-affinity column. The use of the Millipore Filter Device for protein concentration gave a 16% ( p < 0.005) higher recovery of protein in flow-through sample compared with acetone precipitation. The use of OptiPrep gave the lowest level of platelet contamination (1:0.8) during the isolation of PBMC from blood. Several proteins (among which are alpha-tropomyosin, fibrinogen and coagulation factor XIII A) were identified that may be used as biomarkers of platelet contamination in future studies. When identifying preselected spots, at least three out of the four centers found similar identities for 10 out of the 10 plasma proteins, 8 out of the 10 platelet proteins and 8 out of the 10 PBMC proteins. The discrepancy in spot identifications has been described before and may be explained by the mis-selection of spots due to laboratory-to-laboratory variation in gel formats, low scores on the peptide analysis leading to no or only tentative identifications, or incomplete resolution of different proteins in what appears as a single abundant spot. The average within-laboratory coefficient of variation (CV) for each of the matched spots after automatic matching using either PDQuest or ProteomWeaver software ranged between 18 and 69% for depleted plasma proteins, between 21 and 55% for platelet proteins, and between 22 and 38% for PBMC proteins. Subsequent manual matching improved the CV with on average between 1 and 16%. The average between laboratory CV for each of the matched spots after automatic matching ranged between 4 and 54% for depleted plasma proteins, between 5 and 60% for platelet proteins, and between 18 and 70% for PBMC proteins. This variation must be considered when designing sufficiently powered studies that use proteomics tools for biomarker discovery. The use of tricine in the running buffer for the second dimension appears to enhance the resolution of proteins especially in the high molecular weight range.     

Initial proteome analysis of mature barley seeds and malt

Several barley (Hordeum vulgare) cultivars are used in the production of malt for brewing. The malt quality depends on the cultivar, its growth and storage conditions, and the industrial process. To enhance studies on malt quality, we embarked on a proteome analysis approach for barley seeds and malt. The proteome analysis includes two-dimensional (2-D) gel electrophoresis, mass spectrometry, and bioinformatics for identification of selected proteins. This project initially focused on proteins in major spots in the neutral isoelectric point range (pI 4-7) including selected spots that differ between four barley cultivars. The excellent malting barley cultivar Barke was used as reference. Cultivar differences in the 2-D gel spot patterns are observed both at the seed and the malt level. In seed extracts one of the proteins causing variations has been identified as an alpha-amylase/trypsin inhibitor. In malt extracts multiple forms of the alpha-amylase isozyme 2 have been identified in varying cultivar characteristic spot patterns. The present identification of proteins in major spots from 2-D gels includes 27 different proteins from 42 spots from mature seed extract, while only three specific proteins were identified by analysing 13 different spots from the corresponding malt extract. It is suggested that post-translational processing causes the same protein to occur in different spots.     

Analyses of genetic variants of l-glycerol-3-phosphate dehydrogenase in Drosophila melanogaster by two-dimensional gel electrophoresis and immunoelectrophoresis

A protein spot corresponding to l-glycerol-3-phosphate dehydrogenase (α-GPDH, E.C. 1.1.1.8, NAD⁺ oxidoreductase) has been identified on a two-dimensional gel (isoelectric focusing-SDS gel) containing up to 150 stained protein spots from a crude Drosophila homogenate. Preliminary identification of the α-GPDH spot was made by including a suitable amount of purified Drosophila α-GPDH in crude fly homogenates prior to electrophoresis and observing an intensity enhancement of the corresponding protein spot on the gels. When three purified electrophoretic variants (slow, fast, and ultrafast) were mixed and analyzed by two-dimensional gel electrophoresis, horizontal displacements of the three protein spots were observed. Immunoprecipitation of the enzyme prior to electrophoresis and gene mapping further confirmed the identity of the α-GPDH protein spot. The α-GPDH spot can also be detected by autoradiography of a two-dimensional gel from a single fly extract, where it has been estimated to constitute 0.5–1% of the total soluble protein. Mutants which express no apparent α-GPDH activity were analyzed by two-dimensional gels and immunoelectrophoresis in an attempt to identify and characterize the inactive proteins. It is suggested that these techniques provide a powerful tool for the analysis of CRM⁺-null activity mutants of a specific gene-enzyme system.     

A multiple high-resolution mini two-dimensional polyacrylamide gel electrophoresis system: imaging two-dimensional gels using a cooled charge-coupled device after staining with silver or labeling with fluorophore.

A multiple mini two-dimensional electrophoretic method which results in three two-dimensional protein spot patterns being positioned side by side in an individual gel has been developed. Preparation time has been minimized by employing disposable capillary tubes for the isoelectric focusing gels and reducing the number of second-dimensional gels required. Commercially available vertical slab units were used for the second-dimensional electrophoresis. The protein spot patterns were visualized either by staining the second-dimensional gel with silver or fluorescently labeling the focused proteins while present in the isoelectric focusing gel and subsequently electrophoresing them into the second-dimensional gel. The fluorescently labeled second-dimensional gel was imaged while still present in the glass mold immediately following electrophoresis. Two fluorophores were compared: 2-methoxy-2,4-diphenyl-3(2H)-furanone and 5-(4,6-dichlorotriazin-2-yl)aminofluorescein hydrochloride. A rapid imaging system based on a cooled charge-coupled device was used to view both the silver-stained and fluorescently labeled two-dimensional spot patterns. The sensitivity of detection of protein spots in the mini two-dimensional gels was similar for the two types of fluorescently labeled gels and the silver-stained gels.     

The myth of automated, high-throughput two-dimensional gel analysis

Many software packages have been developed to process and analyze 2-D gel images. Some programs have been touted as automated, high-throughput solutions. We tested five commercially available programs using 18 replicate gels of a rat brain protein extract. We determined computer processing time, approximate spot editing time, time required to correct spot mismatches, as well as total processing time. We also determined the number of spots automatically detected, number of spots kept after manual editing, and the percentage of automatically generated correct matches. We also determined the effect of increasing the number of replicate gels on spot matching efficiency for two of the programs. We found that for all programs tested, less than 3% of the total processing time was automated. The remainder of the time was spent in manual, subjective editing of detected spots and computer generated matches. Total processing time for 18 gels varied from 22 to 84 h. The percentage of correct matches generated automatically varied from 1 to 62%. Increasing the number of gels in an experiment dramatically reduced the percentage of automatically generated correct matches. Our results demonstrate that these 2-D gel analysis programs are not automatic or rapid, and also suggest that matching accuracy decreases as experiment size increases.     

Using standard positions and image fusion to create proteome maps from collections of two-dimensional gel electrophoresis images

Databases for two-dimensional protein gels pose new challenges in extracting meaningful information from large numbers of experiments. In order to create expression profiles, positions of corresponding protein spots across all gel images have to be established. In larger gel sets errors may accumulate rapidly during this spot matching process, effectively limiting the number of samples available for data mining. Here we present a novel approach for organizing spot data based on the concept of a standard position for a protein species. Standard positions are meaningful average positions that are determined using all occurrences of a protein species. They can be extended to spots that are not annotated via interpolation. The standard position of a spot can serve as a unifying index across all gels in a database, thus allowing creation and analysis of expression profiles that span the whole collection. The standard position gives a much more accurate estimation of a spot's position on a gel than can be obtained using theoretical isoelectric point and molecular weight. Positional indexing is a complement to a priori identifications (e.g. by mass spectrometry or Edman degradation). Moreover it can be used in advance to select spots that are worth identifying because they show relevant expression profiles. Furthermore, we show how to combine all spots that occur on any of the gels into one synthetic but nevertheless realistic-looking image. This composite image is produced such that all spots have their standard positions. It can serve as a proteome reference map for an organism. As an application, we have computed a reference map from 23 gel images of Bacillus subtilis, using an enhanced prerelease version of the gel analysis software Delta2D (DECODON, Greifswald, Germany).     

Computer analysis of double-labeled two-dimensional electrophoresis gels

A computerized process for the automatic analysis of double-label autoradiography after two-dimensional polyacrylamide gel electrophoresis has been developed. Matching fluorographs and autoradiographs produced from gels containing 3H- and 14C-labeled proteins are digitized by a rotating drum densitometer and analyzed by the Man-computer Interactive Data Analysis System III. This system locates corresponding protein spots in the films with edge-detection algorithms, converts spot density readings to isotopic disintegrations by reference to standard curves, and computes a 3H:14C ratio for each spot in the gels. On the average, calculated ratios are accurate to approximately 9% for test strips of polyacrylamide gel containing uniform mixtures of 3H and 14C. Values obtained for two-dimensional gels containing n protein spots with a known 3H:14C ratio of 8.6 +/- 0.1 are as follows: 8.1 +/- 1.4 (n = 268), 8.8 +/- 2.1 (n = 278), 9.1 +/- 1.7 (n = 245), and 8.8 +/- 2.2 (n = 223). The computer process greatly reduces the time required to precisely compare two complex protein mixtures and has sufficient precision to detect a doubling in the biosynthesis of any individual protein.     

Identification of PSME3 as a novel serum tumor marker for colorectal cancer by combining two-dimensional polyacrylamide gel electrophoresis with a strictly mass spectrometry-based approach for data analysis

The purpose of this study was to identify and validate novel serological protein biomarkers of human colorectal cancer (CRC). Proteins from matched CRC and adjacent normal tissue samples were resolved by two-dimensional gel electrophoresis. From each gel all spots were excised, and enveloped proteins were identified by MS. By comparison of the resulting protein profiles, dysregulated proteins can be identified. A list of all identified proteins and validation of five exemplarily selected proteins, elevated in CRC was reported previously (Roessler, M., Rollinger, W., Palme, S., Hagmann, M. L., Berndt, P., Engel, A. M., Schneidinger, B., Pfeffer, M., Andres, H., Karl, J., Bodenmuller, H., Ruschoff, J., Henkel, T., Rohr, G., Rossol, S., Rosch, W., Langen, H., Zolg, W., and Tacke, M. (2005) Identification of nicotinamide N-methyltransferase as a novel serum tumor marker for colorectal cancer. Clin. Cancer Res. 11, 6550-6557). Here we describe identification and initial validation of another potential marker protein for CRC. Comparison of tissue protein profiles revealed strong elevation of proteasome activator complex subunit 3 (PSME3) expression in CRC tissue. This dysregulation was not detectable based on the spot pattern. The PSME3-containing spot on tumor gels showed no visible difference to the corresponding spot on matched control gels. MS analysis revealed the presence of two proteins, PSME3 and annexin 4 (ANXA4) in one and the same spot on tumor gels, whereas the matched spot contained only one protein, ANXA4, on control gels. Therefore, dysregulation of PSME3 was masked by ANXA4 and could only be recognized by MS-based analysis but not by image analysis. To validate this finding, antibody to PSME3 was developed, and up-regulation in CRC was confirmed by Western blot analysis and immunohistochemistry. Finally by developing a highly sensitive immunoassay, PSME3 could be detected in human sera and was significantly elevated in CRC patients compared with healthy donors and patients with benign bowel disease. We propose that PSME3 be considered a novel serum tumor marker for CRC that may have significance in the detection and in the management of patients with this disease. Further studies are needed to fully assess the potential clinical value of this marker candidate.     

Hierarchical grid transformation for image warping in the analysis of two-dimensional electrophoresis gels

Two-dimensional electrophoresis is a widely used method for separating a large number of proteins from complex protein mixtures and for revealing differential patterns of protein expressions. In the computer-assisted proteome research, the comparison of protein separation profiles involves several heuristic steps, ranging from protein spot detection to matching of unknown spots. An important prerequisite for efficient protein spot matching is the image warping step, where the geometric relationship between the gel profiles is modeled on the basis of a given set of known corresponding spots, so-called landmarks, and the locations of unknown spots are predicted using the optimized model. Traditionally, polynomial functions together with least squares optimization has been used, even though this approach is known to be incapable of modeling all the complex distortions inherent in electrophoretic data. To satisfy the need of more flexible gel distortion correction, a hierarchical grid transformation method with stochastic optimization is presented. The method provides an adaptive multiresolution model between the gels, and good correction performance in the practical cross-validation tests suggests that automatic warping of gel images could be based on this approach. We believe that the proposed model also has significance in the ultimate comparison of corresponding protein spots since the matching process should benefit from the closeness of the true spot pairs.     

The state of the art in the analysis of two-dimensional gel electrophoresis images

Software-based image analysis is a crucial step in the biological interpretation of two-dimensional gel electrophoresis experiments. Recent significant advances in image processing methods combined with powerful computing hardware have enabled the routine analysis of large experiments. We cover the process starting with the imaging of 2-D gels, quantitation of spots, creation of expression profiles to statistical expression analysis followed by the presentation of results. Challenges for analysis software as well as good practices are highlighted. We emphasize image warping and related methods that are able to overcome the difficulties that are due to varying migration positions of spots between gels. Spot detection, quantitation, normalization, and the creation of expression profiles are described in detail. The recent development of consensus spot patterns and complete expression profiles enables one to take full advantage of statistical methods for expression analysis that are well established for the analysis of DNA microarray experiments. We close with an overview of visualization and presentation methods (proteome maps) and current challenges in the field. An erratum to this article can be found at     

Comparative proteomics analysis of human lung squamous carcinoma

Two-dimensional polyacrylamide gel electrophoresis (2-DE) profiles of human lung squamous carcinoma tissue and paired surrounding normal bronchial epithelial tissue were compared. Selected differential protein-spots were identified with peptide mass fingerprinting based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) and database searching. Well-resolved and reproducible 2-DE patterns of both the tumor and the normal tissues were acquired. The average deviations of spot position were 0.873+/-0.125mm in IEF direction and 1.025+/-0.213mm in SDS-PAGE direction, respectively. For the tumor tissues, a total of 1349+/-67 spots were detected and 1235+/-48 spots were matched with an average matching rate of 91.5%. For the corresponding normal tissues, a total of 1297+/-73 spots were detected and 1183+/-56 spots were matched with an average matching rate of 91.2%. A total of 1069+/-45 spots were matched between the tumor and the normal tissues. Forty differential proteins between tumor and normal tissues were characterized. Some proteins were the products of oncogenes and others were involved in the regulation of cell cycle and signal transduction. These data are valuable for mass identification of differentially expressed proteins involved in lung carcinogenesis, establishing human lung cancer proteome database and screening molecular marker to further study human lung squamous carcinoma.