How many spots with missing values can be tolerated in quantitative two-dimensional gel electrophoresis when applying univariate statistics?

Quantitative proteomic comparisons require a sufficient number of samples to reach an acceptable level of significance. But 2D gel electrophoresis commonly results in incomplete data sets due to spots with missing values reducing thereby the number of parallel measurements for individual proteins. Here we investigated how many missing values per spot can be tolerated. The number of spots in common between all gels was found to decrease with the number of parallel gels in a non-linear fashion. Increasing numbers of missing values were associated with a moderate increase in the quantitative variation of spot volumes. Based on the missing value pattern in 20 gels we performed an analysis of the multiple testing power for the hypothetical scenario of a comparative 2DE study with six or twelve parallel gels. The calculation considered the statistical power of the individual spot as well as the number of spots included in the analysis. The power increased with inclusion of spots with higher number of missing values and showed an optimum at a specific minimum number of spot replicates. The results suggest that proteins with missing values can be included in a univariate analysis as long as a sufficient number of parallel gels are made.     

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.     

Challenges related to analysis of protein spot volumes from two-dimensional gel electrophoresis as revealed by replicate gels

Assumptions that need to be considered prior to statistical analysis of protein spot volumes from two-dimensional gel electrophoresis (2-DE) data are studied using replicate gels of the same sample. The most important observation is that the data tables of protein spot volumes from 2-DE images contain a large number of missing values, which are not consistent with the presence or absence of the proteins. This implies both loss of information and problems for the subsequent statistical analysis. Challenges with 2-DE protein spot volumes are viewed in light of multiple gel comparisons and multivariate data analysis.     

Sources of Variability among Replicate Samples Separated by Two-Dimensional Gel Electrophoresis

Two-dimensional gel electrophoresis (2DE) offers high-resolution separation for intact proteins. However, variability in the appearance of spots can limit the ability to identify true differences between conditions. Variability can occur at a number of levels. Individual samples can differ because of biological variability. Technical variability can occur during protein extraction, processing, or storage. Another potential source of variability occurs during analysis of the gels and is not a result of any of the causes of variability named above. We performed a study designed to focus only on the variability caused by analysis. We separated three aliquots of rat left ventricle and analyzed differences in protein abundance on the replicate 2D gels. As the samples loaded on each gel were identical, differences in protein abundance are caused by variability in separation or interpretation of the gels. Protein spots were compared across gels by quantile values to determine differences. Fourteen percent of spots had a maximum difference in intensity of 0.4 quantile values or more between replicates. We then looked individually at the spots to determine the cause of differences between the measured intensities. Reasons for differences were: failure to identify a spot (59%), differences in spot boundaries (13%), difference in the peak height (6%), and a combination of these factors (21). This study demonstrates that spot identification and characterization make major contributions to variability seen with 2DE. Methods to highlight why measured protein spot abundance is different could reduce these errors.     

Assessment of protein spot components applying correspondence analysis for peptide mass fingerprint data

Proteins separated by two-dimensional gel electrophoresis (2-DE) may be distributed over several spots. Otherwise, one spot may contain more than one component. The same protein occurring in several spots supposedly represents differently modified protein species that might be of biological relevance. Identification of spots with peptide mass fingerprinting and database searching leads only to the detection of the major spot components. If a spot also contains additional minor protein components, quantitation of spots with protein staining techniques or antibody detection becomes misleading. In order to find spots containing minor components we applied correspondence analysis, a multivariate data exploration method, to peptide mass fingerprint data. Correspondence analysis using peak lists revealed groups of spots containing the same protein with their characteristic mass-to-charge ratio (m/z) values. In order to detect different protein spot components an interactive threshold setting and removal of m/z values with subsequent recalculation of the correspondence analysis using our software tool CorrAn are performed. The usefulness of this methodical approach was shown by a data set of peptide mass fingerprints of 284 spots of Helicobacter pylori 26695 separated by 2-DE.     

The holm oak leaf proteome: analytical and biological variability in the protein expression level assessed by 2-DE and protein identification tandem mass spectrometry de novo sequencing and sequence similarity searching

As a first approach in establishing the holm oak leaf proteome, we have optimised a protocol for this plant and tissue which includes the following steps: trichloroacetic acid-acetone extraction, two-dimensional gel electrophoresis (2-DE) on pH 5 to 8 linear gradient immobilised pH gradient strips as the first dimension, and sodium dodecyl sulfate-polyacrylamide gel electrophoresis on 13% polyacrylamide gels as the second one. Proteins were detected by Coomassie staining. Gel images were recorded and digitalized, and the protein spots quantified by using a linear regression equation of protein quantity on spot volume obtained against standard proteins. Analytical variance was calculated for one-hundred protein spots from three replicate 2-DE gels of the same protein extract. Biological variance was determined for the same protein spots from independent tissue extracts corresponding to leaves from different trees, or the same tree at different orientations or sampling times during a day. Values of 26% for the analytical variance and 58.6% for the biological variance among independent trees were obtained. These values provide a quantified and statistical basis for the evaluation of protein expression changes in comparative proteomic investigations with this species. A representative set of the major proteins, covering the isoelectric point range of 5 to 8 and the relative molecular mass(r) range of 14 to 78 kDa, were subjected to liquid chromatography-tandem mass spectrometry analysis. Due to the absence of Quercus DNA or protein sequence databases, a method based on the procedure reported by Liska and Shevchenko including de novo sequencing and BLAST similarity searching against other plant species databases was used for protein identification. Out of 43 analysed spots, 35 were positively identified. The identified proteins mainly corresponded to enzymes involved in photosynthesis and energetic metabolism, with a significant number corresponding to RubisCO.     

Pinnacle: a fast, automatic and accurate method for detecting and quantifying protein spots in 2-dimensional gel electrophoresis data

MOTIVATION: One of the key limitations for proteomic studies using 2-dimensional gel electrophoresis (2DE) is the lack of rapid, robust and reproducible methods for detecting, matching and quantifying protein spots. The most commonly used approaches involve first detecting spots and drawing spot boundaries on individual gels, then matching spots across gels and finally quantifying each spot by calculating normalized spot volumes. This approach is time consuming, error-prone and frequently requires extensive manual editing, which can unintentionally introduce bias into the results. RESULTS: We introduce a new method for spot detection and quantification called Pinnacle that is automatic, quick, sensitive and specific and yields spot quantifications that are reliable and precise. This method incorporates a spot definition that is based on simple, straightforward criteria rather than complex arbitrary definitions, and results in no missing data. Using dilution series for validation, we demonstrate Pinnacle outperformed two well-established 2DE analysis packages, proving to be more accurate and yielding smaller coefficiant of variations (CVs). More accurate quantifications may lead to increased power for detecting differentially expressed spots, an idea supported by the results of our group comparison experiment. Our fast, automatic analysis method makes it feasible to conduct very large 2DE-based proteomic studies that are adequately powered to find important protein expression differences. AVAILABILITY: Matlab code to implement Pinnacle is available from the authors upon request for non-commercial use.     

Evaluation of individual protein errors in silver-stained two-dimensional gels

The relationship between spot volume and variation for all protein spots observed on large format 2D gels when utilising silver stain technology and a model system based on mammalian NSO cell extracts is reported. By running multiple gels we have shown that the reproducibility of data generated in this way is dependent on individual protein spot volumes, which in turn are directly correlated with the coefficient of variation. The coefficients of variation across all observed protein spots were highest for low abundant proteins which are the primary contributors to process error, and lowest for more abundant proteins. Using the relationship between spot volume and coefficient of variation we show it is necessary to calculate variation for individual protein spot volumes. The inherent limitations of silver staining therefore mean that errors in individual protein spot volumes must be considered when assessing significant changes in protein spot volume and not global error.     

蛋白负染方法在蛋白质组学中的应用评价

为评价蛋白质负染方法在蛋白质组学分析中的应用,采用负染和考马斯亮蓝染色两种方法对同一样品的双向电泳胶进行染色,取相对应的8对蛋白点,并进行胶内酶解及MALDI-TOF/TOF分析,比较两种方法与质谱的兼容性。图像分析显示,负染方法展示出的蛋白点更多,但三维峰图不如考染明晰;质谱结果显示,8个负染蛋白点中有7个鉴定结果有效,8个考染蛋白点鉴定结果均有效。因此可以得出以下结论:负染的灵敏度高于考染,与质谱的兼容性良好,适用于建立双向电泳参考图谱的研究;但负染后的胶图不适于进行蛋白点丰度对比分析。     

An improved mechanically durable electrophoresis gel matrix that is fully compatible with fluorescence-based protein detection technologies

Unfortunately, conventional large-format polyacrylamide gels are mechanically fragile, often tearing during the subsequent manipulations required for visualization of the proteins. This problem is compounded when large-format two-dimensional gels are subjected to multiple staining procedures in order to detect different classes of proteins, such as total protein, phosphoproteins, and glycoproteins. A mechanically durable liquid polyacrylamide-based matrix has been developed that, upon polymerization, facilitates the handling of one-dimensional and two-dimensional gels. The matrix, referred to as Rhinohide liquid acrylamide, is stable as a refrigerated solution for up to one year, and forms a polymer-reinforced polyacrylamide gel suitable for electrophoresis, upon addition of catalysts. The matrix is superior to previously reported durable gel matrices in that it does not cause distortion of high-molecular-weight bands and does not suffer from other spot morphology artifacts, such as doubling of protein spots in the molecular weight dimension. The matrix is particularly valuable for the analysis of proteins applying multiple applications of fluorescent dyes, as required with serial staining of proteins for phosphorylation, glycosylation, and total protein expression, using Pro-Q Diamond phosphoprotein stain, Pro-Q Emerald glycoprotein stain and SYPRO Ruby protein gel stain, respectively.     

Proteome analysis of rat hippocampal neurons by multiple large gel two-dimensional electrophoresis

The goal of the present study was to detect as many protein spots as possible in mammalian cells using two-dimensional gel electrophoresis (2-DE). For proteome analysis, it is of importance to reveal as many proteins as possible. A single standard 2-DE gel (pH 3-10, 18 cm x 20 cm, 13.5% gel) could detect 853 spots from proteins of cultured rat hippocampal neurons when visualized by silver staining. To increase the resolution of the separation and the number of detectable proteins by 2-DE, we utilized seven different narrow pH range immobilized pH gradients in the first dimension. In the second dimension, fourteen long SDS polyacrylamide gels were used: seven 7.5% gels for the separation of high molecular mass proteins (> or = 40 kDa) and seven 13.5% gels for the separation of low molecular mass proteins (< or = 40 kDa). Three hundred and sixty microg of proteins from cultured hippocampal neurons were loaded on to individual gels and visualized by silver staining. All 14 gel images were assembled into a 70 cm x 67 cm cybergel that contained 6677 protein spots, thereby indicating that the utilization of the present strategy led to a 783% increase in the number of detected spots in comparison to the standard procedure. Loading double the amount (720 microg) of proteins on to a 13.5% gel led to a 184% increase in the number of detected spots, thereby indicating that the present strategy has a potential to display more protein spots in the cybergels.     

The QUEST system for quantitative analysis of two-dimensional gels

The strategies and methods used by the QUEST system for two-dimensional gel analysis are described, and the performance of the system is evaluated. Radiolabeled proteins, resolved on two-dimensional gels and detected using calibrated exposures to film, are quantified in units of disintegrations per minute or as a fraction of the total protein radioactivity applied to the gel. Spot quantitation and resolution of overlapping spots is performed by two-dimensional gaussian fitting. Pattern matching is carried out for groups of gels called matchsets, and within each matchset every gel is matched to every other gel. During the matching process, spots are automatically added to each pattern at positions where unmatched spots were detected in other patterns. This results in enhanced accuracy for both spot detection and for matching. The spot fitting procedure is repeated after matching. Tests show that up to 97% of spots in each pattern can be matched and that fewer than 1% of the spots are matched inconsistently. Approximately 2000 proteins are detected from typical gels. Of these 1600 are high quality spots. Tests to measure the coefficient of variation of spot quantitation versus spot quality show that the average coefficient of variation for high quality spots is 21%. The intensities of the detected proteins range from 4 to 20,000 ppm of total protein synthesis. The QUEST analysis system has been used to build a quantitative database for the proteins of normal and transformed REF52 cells, as presented in the accompanying reports (Garrels, J., and Franza, B. R., Jr. (1989) J. Biol. Chem. 264, 5283-5298, 5299-5312).     

Mass spectrometry-based label free quantification of gel separated proteins

Co-migrating proteins in 2D PAGE spots cause difficulties in the assignment of quantitative data obtained from the staining density of a gel spot. We present an application of a label free LC-MS quantitative method that can overcome problems like this. Protein mixtures were prepared with varying compositions, and were run on either 1D or 2D PAGE. Relative and absolute quantitative evaluation was carried out using a simple but reliable method based on integrated MS signals of the three most intensive peptides of each protein. The efficacy of digestion and peptide extraction is, however, influenced by different factors in gel from those in solution, hence the method had to be validated via a quantitative assessment of proteins from 1D or 2D gels. Our findings suggest that a reliable relative quantification is viable using peptide ion intensities when protein levels in two gels have to be compared. In the case of 2D gels, label free MS quantification provides more precise results on changes of protein expression levels than gel spot intensity-based measurements, especially in the case of overlapping proteins. Absolute amounts of different proteins in 1D or 2D gels can be evaluated to a reasonable precision.     

Computer analysis of two-dimensional gels.

This work identifies statistical algorithms which need to be included in analysis of two-dimensional gels for accurate determination of differential changes. Two-dimensional electrophoresis is a powerful tool for determining differential protein expression in complex mixtures, but the methodology, to date, is not producing expected results due to the degree of gel variability. The new DIGE procedure, comparing two samples in the same gel, does eliminate some of the variability introduced with gel-to-gel comparison, but still has variability due to differences in dye binding, charge, and fluorescence. Introducing quality-assurance statistical algorithms is necessary to extract meaningful data from the gels. A quality-control analysis of replicate gels needs to be performed prior to using the set in the final analysis. Increasing replicates to five from the usual three can only add greater variability. A statistical "replicate quality" gel test needs to be done on the computer gel scans, and replicates with greater than 20-30% variability should not be used. In addition, since spot intensity data are not normally distributed, spot differential analysis cannot be a t-test. The Studentized Range has been suggested as a more accurate method for calculating significant difference.     

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).     

Normalization and analysis of residual variation in two-dimensional gel electrophoresis for quantitative differential proteomics

Although two-dimensional gel electrophoresis (2-DE) has long been a favorite experimental method to screen proteomes, its reproducibility is seldom analyzed with the assistance of quantitative error models. The lack of models of residual distributions that can be used to assign likelihood to differential expression reflects the difficulty in tackling the combined effect of variability in spot intensity and uncertain recognition of the same spot in different gels. In this report we have analyzed a series of four triplicate two-dimensional gels of chicken embryo heart samples at two distinct development stages to produce such a model of residual distribution. In order to achieve this reference error model, a nonparametric procedure for consistent spot intensity normalization had to be established, and is also reported here. In addition to variability in normalized intensity due to various sources, the residual variation between replicates was observed to be compounded by failure to identify the spot itself (gel alignment). The mixed effect is reflected by variably skewed bimodal density distributions of residuals. The extraction of a global error model that accommodated such distribution was achieved empirically by machine learning, specifically by bootstrapped artificial neural networks. The model described is being used to assign confidence values to observed variations in arbitrary 2-DE gels in order to quantify the degree of over-expression and under-expression of protein spots.     

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.     

Entamoeba histolytica: analysis of the trophozoite proteome by two-dimensional polyacrylamide gel electrophoresis

The Entamoeba histolytica genome project carried out at TIGR and the Sanger Institute has produced a near-complete set of deduced open reading frame sequences. These data provide strong support for the identification of signals from proteomic analyses such as two-dimensional electrophoresis by protein sequencing and/or mass spectrometric methods. To carry out an initial investigation of the E. histolytica proteome, appropriate sample preparation and silver staining protocols were adapted. After preparation of protein extracts from E. histolytica HM-1:IMSS trophozoites, solubilized proteins were separated in the first dimension in IPG (immobilized pH gradient) strips depending on their pI and subsequently in the second dimension according to their molecular weight by SDS-polyacrylamide gel electrophoresis. Of the more than 1500 protein spots visualized, several landmark spots were isolated from the gels and identified by either tryptic cleavage and subsequent MALDI-TOF mass spectrometry or by protein sequencing.     

Multivariate data analysis of two-dimensional gel electrophoresis protein patterns from few samples

One application of 2D gel electrophoresis is to reveal differences in protein pattern between two or more groups of individuals, attributable to their group membership. Multivariate data analytical methods are useful in pinpointing the spots relevant for discrimination by focusing not only on single spot differences, but on the covariance structure between proteins. However, their outcome is dependent on data scaling, and they may fail in producing valid multivariate models due to the much higher number of "irrelevant" spots present in the gels. The case where only few gels are available and where the aim is to find as many as possible of the group-dependent proteins seems particularly difficult to handle. The present paper investigates such a case regarding the effect of scaling and of prefiltering by univariate nonparametric statistics on the selection of spots. Besides, a modified 'autoscaling' of the full data set based on within-group standard deviations is introduced and shown to be advantageous in revealing potential group-dependent proteins additional to those found by prefiltering.     

Polar electrophoresis: shape of two-dimensional maps is as important as size

The performance of two-dimensional electrophoresis in conventional gels in Cartesian coordinates (2-DE) vs. polar coordinates (2-PE) is here evaluated. Although 2-DE is performed in much longer Immobiline gels in the first dimension (17 cm) vs. barely 7-cm in 2-PE, an equivalent resolving power is found. Moreover, due to the possibility of running up to seven Immobiline strips in the radial gel format, the reproducibility of spot position is seen to be higher, this resulting in a 20% higher matching efficiency. As an extra bonus, strings of "isobaric" spots (i.e. polypeptides of identical mass with different pI values) are more resolved in the radial gel format, especially in the 10 to 30 kDa region, where the gel area fans out leaving extra space for spot resolution. In conclusion, this novel gel format in the second dimension of 2D gels is seen as an important improvement of this technique, still one of the most popular in proteome analysis.