Quantitative Gel Electrophoresis: Sources of ... - ACS Publications

38124 Braunschweig, Germany, and Institute for Human Genetics, Charité-University Medicine Berlin,. Augustenburger Platz 1, 13353 Berlin, Germany...
1 downloads 0 Views 489KB Size
Quantitative Gel Electrophoresis: Sources of Variation Simone Schröder,† Hui Zhang,‡ Edward S. Yeung,‡ Lothar Jänsch,§ Claus Zabel,4 and Hermann Wätzig*,† Institute of Pharmaceutical Chemistry, TU Braunschweig, Beethovenstrasse 55, 38106 Braunschweig, Germany, Iowa State University, Ames, Iowa, 50011, Helmholtz Centre for Infection Research, Inhoffenstrasse 7, 38124 Braunschweig, Germany, and Institute for Human Genetics, Charité-University Medicine Berlin, Augustenburger Platz 1, 13353 Berlin, Germany Received September 10, 2007

Gel electrophoresis is known for its often unsatisfactory precision. Percental relative standard deviations (RSD%) in a range of 15–70% have been reported. Therefore, an improvement of precision in quantitative 2-DE is necessary. In the present, study we have analyzed the work flow of 2-DE in detail to assess the main error sources. Potential major sources of variability for this technique include the transfer between first and second dimension, the analyst’s expertise, and the staining or rather detection of separated proteins. The remarkable and completely irregular changes of the background signal from gel to gel were identified as one of the governing error sources. These background changes can be strongly reduced by the direct detection of the separated proteins using native fluorescence. More than a 3-fold better signal-to-noise ratio was found compared to Ruthenium-(II)-tris-(bathophenanthroline disulfonat) (RuBPS) and Coomassie staining, although the sample was used in an 800-fold lower concentration. This improvement together with well-defined peaks resulted in a better quantitative spot reproducibility of approximately 12–16% RSD%. Possibly, the variabilities due to detection and evaluation were already reduced to minor error components. However, according to the law of error propagation, the major error sources dominate the total error. To really prove the good detection and evaluation, these other sources of variability such as sample preparation, strip rehydration, protein loading, transfer between dimensions, interactions between gel and proteins, gel scanning, and spot integration have to be reduced next. Keywords: 1-D and 2-D gel electrophoresis • Quantitative analysis • Reproducibility

1. Introduction Gel electrophoresis is a favored separation tool in protein analysis. For a long time, SDS polyacrylamide gel electrophoresis (SDS-PAGE) has been the core analytical technique for the separation of protein molecules, elucidation of molecular weights and structural characteristics, quantitative analysis, and assessment of sample purity. In the 1970s, two-dimensional gel electrophoresis (2-DE) was introduced by O’Farrell1 and Klose2 independently. 2-DE is a powerful technique to simultaneously separate hundreds to thousands of protein species in complex mixtures according to two independent biophysical properties of the proteins. Therefore, 2-DE was established in proteomics to detect and quantify differences between two or more conditions. Comprehensive reviews have been published which underline the high achievement of this technique.3,4 Because of its high analytical capacities, 2-DE has already been applied in many fields of research ranging from clinical * To whom correspondence should be addressed. Phone: +49-531-391 2764. Fax: +49-531-391 2799. E-mail: [email protected]. † Institute of Pharmaceutical Chemistry. ‡ Iowa State University. § Helmholtz Centre for Infection Research. 4 Institute for Human Genetics, Charité-University Medicine Berlin.

1226 Journal of Proteome Research 2008, 7, 1226–1234 Published on Web 01/26/2008

diagnostics over various basic research projects to the development of new drugs. Diseases and the administration of drugs result in characteristic changes of protein patterns. The gel pattern after drug application, for example, basically reflecting both about the therapeutic success and observed side effects. Thus, 2-DE has been established to understand disease mechanisms, to characterize pharmaceutical effects, or to identify therapeutic targets.3,5,6 Particularly, in this case, reproducible and precise analytical methods are of great importance.7 The basic principle of the 2-DE technique has not been changed significantly since its introduction. In the first dimension, proteins are separated according to their isoelectric point (pI) by isoelectric focusing (IEF). Disulfide bonds are cleaved by a reducing agent, and subsequently, the reduced thiol groups are alkylated to prevent reoxidation during further electrophoresis. The protein subunits are solubilized and associated with sodium dodecyl sulfate (SDS) molecules in nearly constant relative ratios. Thus, negatively charged protein-SDS complexes are formed which are separated according to their molecular weight in the second dimension by SDS-PAGE. The quantification of separated proteins requires direct or indirect detection and visualization strategies. For this purpose, 10.1021/pr700589s CCC: $40.75

 2008 American Chemical Society

research articles

Quantitative Gel Electrophoresis/Sources of Variation 8–11

various methods are available: staining with dyes such as Coomassie Brilliant Blue (CCB), silver or fluorescent dyes, radioactive labeling (with 14C, 3H, 35S, etc.), or native fluorescence detection. CBB staining has become most popular due to its low cost, easy performance, and good compatibility with downstream characterization methods such as mass spectrometry. The sensitivities of the staining methods are different; CBB and fluorescence staining are less sensitive than silver staining. A common big drawback of all these methods is the high background staining which requires elaborative destaining methods. However, the limitation of sensitivity is a direct consequence of this high background signal, especially for the silver staining method. Since the latter method has no end point, the intensity depends on the duration of staining, which is chosen arbitrarily according to various characteristics. If the staining time is too long, the background becomes dark and detection of spots gets much more difficult. Radioactive labeling is the most sensitive method, although long exposure times are required and the detection of proteins is limited to those incorporating radioactive isotopes. Most proteins contain aromatic amino acids such as tryptophan, phenylalanine, and tyrosine which show significant UV absorption between 250 and 300 nm and a fluorescence between 300 and 400 nm, respectively. Because of these properties, a sensitive, direct detection by UV absorption or native fluorescence is possible.12,13 Although achieving high resolution, the entire 2-DE workflow is labor-intensive and time-consuming. 2-DE also shows limited reproducibility. Changes in spot location of individual spots are frequently observed as well as high RSD% values for the observed spot areas. The accurate handling of the delicate 2D gels requires experienced personnel. Thus, the complexity of the 2D gel electrophoresis procedure as well as the many manual handling steps offer many occasions for error. The problem of high variability has existed since the development of the 2-DE technique. The complexity of 2-DE related problems has been frequently demonstrated. Some solutions have been suggested to overcome these difficulties.14 The technical variation of 2-DE experiments results in relative standard deviations (RSD%) ranging from 13 to 40% of total spot intensity. In some particular cases, the RSD% increases up to about 70% RSD%. These are proteins with extreme properties such as very basic or acidic proteins which are located close to border areas of the gel. This problem of limited reproducibility has only been partially solved to this day, though a number of groups have studied the quantitative reproducibility by technical variations, for example, sample preparation, electrophoresis procedure, data acquisition, software options for gel editing and matching, interoperator, and laboratory variability.7,15–18 The introduction of immobilized pH gradients (IPG) for IEF improved reproducibility, handling, resolution, and separation of very acidic and alkaline proteins.19–21 The development of a technique called difference gel electrophore¨ nlü and co-workers22 reduced the gel-to-gel sis (DIGE) by U variability for quantitative comparisons of protein expression levels. DIGE circumvents elaborative destaining methods as well. A further advantage of this technique is that the number of gels run in an experiment is reduced. Up to three protein extracts can be analyzed by labeling each with one of three different fluorescent dyes (Cy2, Cy3, and/or Cy5). One of these labeled extracts acts as an internal standard used for normalization of all spots.23 The standard sample is ideally a mixture of equal amounts of each of the experimental samples being compared. Therefore, a pooled internal standard is created by

mixing aliquots of all samples which is loaded on each gel to improve protein quantification between samples from different gels. All three labeled protein extracts are combined and separated by 2-DE using a single 2D gel. Three gel images are obtained by using the three different excitation wavelengths of the three fluorescent dyes. The images are merged, and the qualitative and quantitative differences between the samples can be determined using a specialized 2D image analysis software. The DIGE technique is a powerful approach which improves gel-to-gel variations. However, it requires very expensive equipment and reagent kits.24 Many software packages are available that claim to provide accurate quantitative data analysis25 to identify and reveal differences between proteins expressed in various tissues. The algorithms of all these packages are different, but they have four basic analysis steps in common: protein spot detection, spot volume determination, gel-to-gel matching of spot patterns, and relative protein quantification. A few publications have compared different software packages or rather the algorithms and reported significant differences.26,27 The investigations of Wheelock and Buckpitt demonstrate that not only the performance of 2-DE itself, but also the postexperimental data analysis results in poor quantitative reproducibility. These authors estimate that about one-third of the total variance of spot quantification can be related to spot integration. In quantitative analysis, reproducibility and precision are important parameters. The determination of these statistical values conduce to the evaluation of the quality of analytes, for example, pharmaceuticals. Without analytical precision, an accurate estimation of changes in an investigated system is impossible. Therefore, an improvement of reproducibility and precision in 2-DE is necessary. For comparison and detection of differences in biological basic research, a reproducibility of about 5% RSD% is sufficient, but for quality assurance in the pharmaceutical industry, a reproducibility corresponding to 2% RSD% for main assays is desirable. In the present study, we have analyzed the work flow of 2-DE in detail to assess the main error sources of variability and to find out way for improving quantitative 2-DE.

2. Materials and Methods 2.1. Experiment 1. 2.1.1. Fluorescent and Coomassie Brilliant Blue Staining. 2.1.1.1. Chemicals. Urea and SDS were purchased from Bio-Rad (Munich, Germany), thiourea and ammonium sulfate from Fluka (Steinheim, Germany). Tris base was acquired from Sigma-Aldrich (Steinheim, Germany) and ammonium persulfate from Serva Electrophoresis GmbH (Heidelberg, Germany). 3-[(3-Cholamidopropyl)dimethylammonio]-1-propanesulfonate (CHAPS), dithiothreitol (DTT), and agarose were obtained from Biomol GmbH (Hamburg, Germany), Complete Protease inhibitor cocktail tablets from Roche Diagnostics (Mannheim, Germany), and iodoacetamide and bromophenol blue from Merck (Darmstadt, Germany). Glycerine, glycine, Coomassie BB-G250 dye, silicone fluid, N,N,N′,N′tetramethylethylenediamine (TEMED), and polyacrylamide were purchased from Roth (Karlsruhe, Germany). Phosphoric acid (85%) and acetic acid were obtained from Riedel-de Haen (Seelze, Germany). Ethanol and methanol were acquired from J.T.Baker (Deventer, The Netherlands). All water used was obtained from a Milli-Q purification system (Membra Pure Astacus, Germany). 2.1.1.2. Visualization. The gels were fixed in a solution containing 30% (v/v) ethanol and 10% (v/v) acetic acid for 24 h, Journal of Proteome Research • Vol. 7, No. 3, 2008 1227

research articles rinsed trice with water for 30 min, and stained with Ruthenium(II)-tris-(bathophenanthroline disulfonat) (RuBPS) for further 24 h in the dark. Synthesis of RuBPS dye and staining method are described elsewhere.28 After staining, the gels were destained in a fixation solution (30% (v/v) ethanol, 10% (v/v) acetic acid) for 24 h, digitalized with a CCD camera (Fuji-Raytest, Straubenhardt, Germany) with an excitation of 420 nm, and stained subsequently by Coomassie blue silver, a modified Neuhoff’s colloidal Coomassie protocol. 29 The gels were stained with the Coomassie blue silver dye solution for 24 h, afterward destained with water for 48 h, and scanned with a Power Look III scanner (Umax, Willich, Germany). During destaining, water was exchanged two times (after 2 h and again after 24 h). 2.1.1.3. Analysis. Quantitative data analysis was performed using two commercial available software packages, Proteomweaver, Bio-Rad, (Munich, Germany), and Delta 2D, DECODON, (Greifswald, Germany) as well as an integration algorithm based on a smoothing cubic spline function and implemented in the software CISS (Correct Integration Software System).30 To be accessible for CISS, gel images had to be converted into dimension reduced electropherograms by using MATLAB. 2.2. Experiment 1a. 2.2.1. 1D Gel Electrophoresis. 2.2.1.1. Sample. A protein mixture containing 0.5 mg/mL each of the following proteins phosphorylase b (Mr 97.0 kDa), glucoseoxidase (Mr 77.0 kDa), BSA (Mr 66.2 kDa), and ovalbumin (Mr 45.0 kDa) was purchased from Sigma-Aldrich (Steinheim, Germany). The proteins were dissolved in a SDS sample buffer containing 10% (w/v) SDS, 5% Sodium-2-mercaptoethanesulfonate (MESNA), and 0.5 M Tris adjusted to pH 6.8. 2.2.1.2. SDS-PAGE. The stacking gel (4.1% acrylamide) was buffered at pH 6.8, the resolving gel (11.3% acrylamide) at pH 8.0. The dimensions of this 1D-gel were 7 cm × 7 cm × 1 mm. SDS-PAGE was started at 120 V for 15 min, then voltage was adjusted to 180 V, and the run was stopped when the dye front was approximately at the bottom of the gel. One liter of the running buffer contains 2.9 g of Tris base, 14.98 g of glycine, and 1.0 g of SDS. 2.3. Experiment 1b. 2.3.1. 2D Gel Electrophoresis. 2.3.1.1. Sample. A protein mixture containing about 30 µg/ mL each of the following eight proteins cytochrome c (pI 9.8, Mr 11.7 kDa), ribonuclease b (pI 9.3, Mr 13.7 kDa), myoglobin (pI 7.5, Mr 17.8 kDa), catalase (pI 7.3, Mr 58.0 kDa), albumin (pI 6.3–6.5, Mr 67.0 kDa), glucoseoxidase (pI 5.5, Mr 77.0 kDa), β-lactoglobulin (pI 5.5, Mr 18.4 kDa), and pepsin (pI 3.2, Mr 34.6 kDa) was purchased from Sigma-Aldrich (Steinheim, Germany). The proteins were dissolved in 10 mL of a solution containing 5.4 g of urea, Serdolit MB-1, 1.5 g of thiourea, 400 mg of CHAPS, 2 mg of Tris, 46 mg of DTT, 10 µL of leupeptin solution (1 mg/mL), and 100 µL of pefablock solution (2.4 mg/ mL). The sample solution was aliquoted and stored at -20 °C until use. 2.3.1.2. Isoelectric Focusing. IPG strips pH 3–10, 180 × 3 × 0.5 mm purchased from Amersham Biosciences (Uppsala, Sweden) and an IPGphorTM-IEF system (GE Healthcare) were used for separation in the first dimension. The IPGphor system is an integrated system where rehydration with sample solution and IEF are performed in an one-step procedure. In total, 375 µL of protein mixture, 5 µL of IPG buffer (pH 3–10), and 2 µL of a bromophenol blue solution were loaded on the IPG strip by in-gel-rehydration.21 IEF was started by rehydration of the IPG strips at 30 V for 14 h. Afterward the voltage was increased 1228

Journal of Proteome Research • Vol. 7, No. 3, 2008

Schröder et al. Table 1. Protocol for Isoelectric Focusing in the First Dimension of 2D Gel Electrophoresis of Experiment 1b step

time

voltage

Rehydration step 1 step 2 step 3 step 4 step 5 step 6 step 7

14 h 3h 3h 3h 1h 20 h 2h till the end

30 V 100 V 300 V 3000 V 5500 V 5500 V 8000 V 8000 V

step and hold gradient gradient gradient gradient step and hold gradient step and hold

to 8000 V by a gradient till a total voltage of 200 kVh was accomplished. The complete IEF protocol is shown in Table 1. 2.3.1.3. SDS-PAGE. After IEF, the IPG strips were equilibrated with DTT (1.0% (w/v)) and iodoacetamide (4.8% (w/v)) SDS containing buffer.21 The second dimension was performed using 12–15% polyacrylamide gels (18 cm × 20 cm × 1 mm) in a vertical Iso Dalt electrophoresis system (Hoefer Scientific Instruments, San Francisco, CA) with a running buffer containing 24 mM Tris base, 0.2 M glycine, and 0.1% SDS. SDS-PAGE was started with a voltage of 80 V; after 1 h, it was arisen up to 100 V and stopped when the dye front was approximately 2 cm from the bottom of the gel. During the complete electrophoresis, the system was cooled at a temperature of 10 °C. 2.4. Experiment 2. 2.4.1. Silver Staining. Brains from 8 week old R6/2 transgenic as well as CBAxC57BI/6 control mice were used. Sample preparation and extraction as well as 2-DE and silver staining were performed as described in detail elsewhere.31–33 2.5. Experiment 3. 2.5.1. Native Fluorescence Detection. A protein mixture of six native proteins, lysozyme, trypsin inhibitor, carbonic anhydrase, ovalbumin, serum albumin, and phosphorylase b was separated by 1-D gel electrophoresis using a miniaturized polyacrylamide gel of the size of 15 mm × 15 mm × 1 mm. The sample preparation, performance of electrophoresis and detection with laser side entry excitation are described in detail elsewhere.13

3. Results and Discussion 3.1. IPG Strip Equilibration. Figure 1 shows a typical gel pattern after separation of the eight proteins described in experiment 1b. In addition to the main spots, some other regions were stained, especially in the area of contact between the IPG strip and the second dimension gel. Because of this observation, an incomplete transfer of the proteins between the first and second dimension came into consideration. Here, the equilibration step, which is necessary prior to the separation in the second dimension, could be the reason. In this step, the focused proteins are loaded with SDS to facilitate the elution of proteins from the IEF strips and to ensure an optimal transfer of the proteins to the second dimension gel. If the saturation of the IPG strips is not sufficient, a quantitative transfer of the proteins onto the SDS gel is not guaranteed. However, a staining and analysis of the used IPG strips demonstrated the complete removal of the proteins from the strips. The elution of the proteins from the IPG strip does not seem to be problematic, but possibly the migration into the second dimension gel. This second step could be improved by an increased SDS concentration of the equilibration buffer. In the following, SDS concentrations of 3%, 5%, and 8% were investigated.

research articles

Quantitative Gel Electrophoresis/Sources of Variation

each protein, n the number of gels, and m the number of considered proteins. By extracting a root of this pooled variance, the total RSD% values of each SDS concentration were obtained. 2 σ ˆpooled ) 2 ˆm ˆ22 + ... + (nm - 1) · σ ˆ21 + (n2 - 1) · σ (n1 - 1) · σ n1 + n2 + ... + nm - m

Figure 1. Typical gel pattern after separation of the eight proteins of experiment 1b. The protein mixture containing each protein in a concentration of about 30 µg/mL was separated by using IPG strips pH 3–10 (180 × 3 × 0.5 mm) in the first dimension. The second dimension was performed using 12–15% polyacrylamide gels (18 cm × 20 cm × 1 mm). The gels were fixed and stained using Ruthenium-(II)-tris-(bathophenanthroline disulfonat) (RuBPS). In addition to the eight main spots, some other regions are stained, especially in the area of contact between the IPG strip and the second dimension gel. The arrow assigns the bromophenol blue solvent front. Key: 1 glucoseoxidase (pI 5.5, Mr 77.0 kDa); 2 albumin (pI 6.3–6.5, Mr 67.0 kDa); 3 catalase (pI 7.3, Mr 58.0 kDa); 4 pepsin (pI 3.2, Mr 34.6 kDa); 5 β-lactoglobulin (pI 5.5, Mr 18.4 kDa); 6 myoglobin (pI 7.5, Mr 17.8 kDa); 7 ribonuclease b (pI 9.3, Mr 13.7 kDa); 8 cytochrome c (pI 9.8, Mr 11.7 kDa).

The percental relative standard deviation (RSD%) was calculated to compare the variation between the different SDS concentrations. The calculation of RSD% is described in eq 1, where σ ˆ is the estimated standard deviation (eq 2), σ ˆ2 the estimated variance (eq 3), and x the estimated arithmetic mean (eq 4) of the sample. RSD% ) σ ˆ )

σ ˆ · 100% x

(1)

√σˆ 2

(2)

n

∑ (x

i

ˆ2 ) σ

- x)2

i)1

n - 1

(3)

n

∑x

i

x )

i)1

n

(4)

In the majority of cases, an improvement of recovery could not be achieved by increasing the SDS concentration. Rather, the optimum value seems to be obtained by a concentration of about 2% to 3% SDS in the equilibration buffer. This assumption is confirmed by considering the total RSD% values of each SDS concentration. These values equal 40.4% RSD% for a concentration of 2% SDS (n ) 8), 40.0% RSD% for 3% SDS (n ) 9), 61.3% RSD% for 5% SDS (n ) 8), and 58.3% RSD% for 8% SDS (n ) 5), respectively. These total RSD% values were calculated by using the pooled variance. Therefore, the RSD% values of each of the eight proteins was squared to yield the variances. All eight variances of the eight proteins of the same SDS concentration were summarized by eq 5, where 2 2 σ the calculated variance of ˆpooled is the pooled variance, σ ˆm

(5)

The separation of proteins with extreme properties as very basic or acidic, hydrophobic proteins, or proteins of large mass prove to be difficult due to aggregation, oxidation, or precipitation as described by McDonough.34 All this can result in the loss of proteins at various stages of gel electrophoresis. The magnitude of loss during 2-DE procedure has previously been investigated by different groups.35,36 Zuo and Speicher reported most of the transfer losses occur at the equilibration step which comprise about 8–10%. The investigations of Zhou and coworkers show that actually 17–24% of the proteins were lost during the equilibration by dissolving in the buffer solution. Furthermore, proteins show least solubility at their pI. After separation in the first dimension, proteins are concentrated on the IPG strip at their isoelectric points. At this point, the proteins possess no net charge, and electrostatic repulsion between the molecules is omitted. This can easily result in aggregation and precipitation. Proteins have to pass through two different interfaces during transfer from first to second dimension gel: from the gel of the IPG strip, first into the agarose gel and from there into the polyacrylamide gel. Proteins feature different solubility behavior in all these media. Therefore, precipitation at the contact surface may easily occur, and complete migration into the second dimension gel cannot be guaranteed any longer. Not only the resolving of the proteins into the buffer, but also the ability of the protein-SDS complexes to migrate completely into the second dimension gel is a big challenge. An improvement of reproducibility can be achieved by preventing oxidation, aggregation, and precipitation during IPG strip equilibration. Different possibilities are imaginable to reach this. Maybe a modification or rather an optimization of the pH-value of the equilibration solution can be effectual. Additives are conceivable possibilities which do not have an impact on the SDS-PAGE itself but which prevent interactions between the protein molecules. For instance the use of tensides or polyols should be investigated in further experiments. 3.2. Visualization of Separated Proteins. For detection, separated proteins have to be visualized. For this purpose, diverse staining methods are available with different sensitivities. Coomassie Brilliant Blue (CCB) and fluorescent staining are equally or less sensitive than silver staining but provide a significantly better dynamic range and signal-to-background ratio for our representative characterization of protein spots. In experiment 1, the proteins were first visualized by fluorescence staining and subsequently by Coomassie blue silver staining, a modified Neuhoff’s colloidal Coomassie staining procedure.29 Dyes are retained at the proteins by hydrophobic and covalent interactions which resulted in colored protein-dye complexes. Therefore, the visual presence is basically correlated with the distribution and the amount of the proteins within the gel matrix. The influence on the formation of the colored complexes and consequently on quantitative analysis was investigated by changing the normal staining conditions as described above (see section 2.1.1.2, Journal of Proteome Research • Vol. 7, No. 3, 2008 1229

research articles

Figure 2. Calculated RSD% values of the different staining methods and different staining and destaining protocols (Fluorescence and Coomassie blue silver staining) used in experiment 1b; number n of runs: n ) 19; “1” indicates single staining and destaining procedure; “2” indicates repeated staining and destaining procedure, this means that the whole procedure was performed twice. The repetition of the whole fluorescence (RuBPS) staining protocol results in much more intensive spots without a stronger background staining which results in lower RSD% values. In contrast, longer staining times of the Coomssie blue silver staining results not only in more insensive spots, but also in a stronger background staining of the gel. This prevents an accurate classification of spot boundaries and deteriorates the spot intensity reproducibility.

Visualization). Variations in volumes of the used solutions did not influence the reproducibility. However, changes in the staining or destaining protocol yielded strongly distinct results. For example, when the whole procedure was performed twice, distinct improvements in spot intensity reproducibility were obtained. The results are illustrated in Figure 2. The calculated RSD% values were plotted against the isoelectric points of the proteins for both methods. The color of the protein-dye complexes is much more intensive without a stronger background staining of the gel for the fluorescence staining method. In contrast, a deterioration of the RSD% values was noticed by staining the gels with Coomassie blue silver twice. In this case, longer staining times resulted not only in more intensive spots, but also in a stronger background coloration, especially in the areas around the spots hindering the accurate classification of spot boundaries. 3.3. Scan-to-Scan Variability. Digital images have to be recorded before analysis and evaluation by a software program. The required scanning process contributes to the total error. The resulting effect on the reproducibility of the scanning procedure was analyzed. Therefore, three scans of each gel of experiment 1 (Figure 1) were digitalized and were subsequently analyzed by the software PROTEOMWEAVER. This investigation of repeated scanning resulted in RSD% values between 1 and 9%, independent from spot intensity and isoelectric point of the proteins. Proteins which showed good precision in one experiment behave completely different in another gel, emphasizing that the precision was not related to the nature of the analyte but only to the gel properties. These results are consistent with previous reports such as the work of Mahon and Dupree17 who also investigated the scan-to-scan reproducibility. They found an error greater than 1% for all intensities of spots but less than 10%. Also the work of Challapalli et al.16 describes such a technical variability of repeated scanning. 3.4. Analysis of Gel Background. To assess the extent of background staining, gel images were converted into dimension-reduced electropherograms by assigning data to each gray value. We investigated fluorescence stained 1D and 2D gels 1230

Journal of Proteome Research • Vol. 7, No. 3, 2008

Schröder et al.

Figure 3. Comparison of two gel images and the corresponding converted gel images into dimension-reduced electropherograms of two different lanes of 1D gel images of experiment 1a. A protein mixture containing four different proteins (0.5 mg/mL) was separated by 1D gel electrophoresis (8 cm × 7 cm × 1 mm gels). After RuBPS staining, the digitalized gel images were converted into a dimension-reduced electropherograms. Strong distinctions of the baseline results in difficulties of peak integration and big differences of peak areas between the gels.

(experiments 1a and 1b) of the same batch; that is, all gels were cast in one step, the same sample and the same sample volume were loaded. The same reagents such as buffer and staining solution were used, parallel operations were done, and all gels were run under the same electrophoretic conditions. After staining, the digitalized gel images were converted into dimension-reduced electropherograms. Therefore, the images were sectioned into small subunits. The 1D gels were segmented lane by lane and the 2D gels into the upper and the lower range of the gel. The data of the gray values were added column by column. In this way, all parts belonging to one spot were detected. Sample electropherograms are shown in Figure 3 for a comparison of lanes between two 1D gels and Figure 4 for comparison of the upper ranges of two different 2D gels. The resulting peaks were integrated by an algorithm which is based on a smoothing cubic spline function and implemented in the software CISS.30 The electropherograms point out strong fluctuations of the gel background indicated by a fluctuating baseline. Strong distinctions of the baseline not only between but also within the electropherograms result in big differences of peak areas between the gels. This was already observed in the converted 1D gels (Figure 3) but becomes much more apparent in the converted electropherograms of 2D gels (Figure 4). These differences cannot be corrected by any integration software. A software should treat various signals differently. However, it cannot be able to correct existing variations. In fact, four peaks should be shown in the electropherogram of the upper range of the 2D gel: pepsin, glucoseoxidase, albumin, and catalase. However, only glucoseoxidase and albumin can be defined accurately. In contrast, pepsin and catalase disappear in the baseline noise and cannot be detected. Further investigations were carried out to check if this high background variability originates only from the staining procedure. Therefore, gels without sample, directly after gel casting, and gels without sample but subjected to the entire electrophoretic separation up to the point of staining were

Quantitative Gel Electrophoresis/Sources of Variation

research articles

Figure 5. 1D-gel image after separation of the protein mixture of experiment 3. The proteins were separated by using miniaturized polyacrylamide gel electrophoresis (15 mm × 15 mm × 1 mm gels) and detected by native fluorescence. The lysozyme analysis of five different concentrations is shown as a dimension-reduced electropherogram. A small fluctuating baseline is detected but also well-defined peaks, which can easily be integrated. This results in an improvement of the signal-to-noise ratio as well as in a better reproducibility of spot intensity.

Figure 4. Comparison of two 2D gel images of experiment 1b. After staining with RuBPS, the digitalized gel images were converted into dimension-reduced electropherograms. Shown is the conversion of the upper ranges of these two different gels. Strong fluctuations of the gel background indicated by a fluctuating baseline becomes here more apparent than in the 1D gels (Figure 3). Four peaks (pepsin, glucoseoxidase, albumin, catalase) should be shown in the electropherograms. But only glucoseoxidase and albumin can be defined accurately. The other proteins disappear in the baseline noise and cannot be detected.

analyzed as well. The freshly cast gels themselves also show fluctuations of background staining, but this effect is boosted conspicuously after staining (data not shown). In experiment 3 (see section 2.5), six proteins were separated using SDS-PAGE and were detected by their inherent capacity to emit fluorescence (native fluorescence) by excitation with a laser beam. A transformation and investigation of these gels was performed using the same method as described above. For instance, a converted electropherogram of lysozyme showing five different concentrations is displayed in Figure 5. A small fluctuation of the baseline is detected as well, but it is not as distinct as for the fluorescence-stained gels (Figures 3 and 4 .). Furthermore, in contrast to conventional staining methods, well-defined peaks were detected which can easily be integrated. These improvements yield to a 3-fold better signal-tonoise ratio, although an 800-fold lower sample concentration was used for experiment 3. In order to show a better quantitative reproducibility of native fluorescence detection, a linear regression analysis was performed. Therefore, two gels, containing the proteins at different concentrations, were prepared. The considered protein concentrations per gel were 0.8, 1.6, 4.0, and 8.0 ng, respectively. Figure 6 shows the observed peak areas subjected to the corresponding protein amounts. The obtained results of the two different gels are plotted with two different symbols. From these data, a regression line was calculated which is shown in Figure 6. On the basis of this

Figure 6. A linear regression analysis was performed to check quantitative reproducibility of native fluorescence detection. Shown are the observed peak areas and the corresponding protein amounts of experiment 3 as well as the calculated regression line. Two different gels were investigated. Each one contains the proteins in four different concentrations (0.8, 1.6, 4.0, and 8.0 ng).

investigation, a better quantitative spot reproducibility can be achieved by native fluorescence detection. An improvement of the signal-to-noise ratio as well as the well-defined peaks resulted in relative standard deviations in a narrow range of approximately 12–16% RSD%. The results of the six investigated proteins are summarized in Table 2. The limit of detection (LOD) is the lowest amount of an analyte in a sample which can be detected and was used here to compare the sensitivities of the different staining methods we investigated. Usually, the LOD is defined using the signalto-noise ratio. The European Pharmacopoeia (Ph. Eur.) suggests a signal-to-noise ratio of three for the LOD.37 This ratio and the corresponding sample amount were estimated of the calculated signal-to-noise ratios of all proteins. In addition to the better quantitative spot reproducibility, the native fluorescence detection also shows a higher sensitivity as a direct consequence of the improvement of the signalto-noise ratio. These estimated LODs or rather estimated lowest amounts which can be detected are 0.3 ng for the Journal of Proteome Research • Vol. 7, No. 3, 2008 1231

research articles

Schröder et al.

Table 2. Results of the Linear Regression analysis (n ) 8) of the six Investigated Proteins of Experiment 3 Using Native Fluorescence Detectiona protein

Mr

pI

RSD%

Lysozyme Trypsin Inhibitor Carbonic Anhydrase Ovalbumin BSA Phosphorylase b

14400 21500 31000 45000 66200 97000

11.7 4.5 6.0 5.1 4.8 6.8

12.0 14.8 16.0 13.3 14.3 15.6

a An improvement of the signal-to-noise ratio as well as the well-defined peaks resulted in a better quantitative spot reproducibility shown in the low percental relative standard deviations (RSD%).

Figure 7. Direct spot-to-spot comparison of the calculated RSD% values of gels of experiment 3 prepared by a trained and an untrained analyst. Both analysts investigated the same sample by using an acidic silver staining. The gels were divided into different pH categories. In the shown pH range of 3.5–4.5, 22 welldefined spots were chosen. Spot intensity increases from spot no. 1 to no. 22. The RSD% values of spots generated by the untrained person were significantly higher.

native fluorescence detection and 0.9 µg for the fluorescence staining method. 3.5. Analyst. The complex technique of 2-DE requires much practice and skill to achieve optimal results. A direct comparison of gels of the same sample prepared by a trained and an untrained person reveals the magnitude of this problem. Each analyst performed eight gels of a complex mice brain extract according to experiment 2. Protein extracts were separated in a pH range of pH 3.5-9.0 in the first dimension and on a 40 cm × 30 cm × 0.9 mm gel in the second dimension. The spots were detected using an acidic silver staining procedure. The gels were divided into five pH categories, and 114 well-defined spots were chosen for this study. The poor gel quality performed by an untrained person is already seen by a visual comparison of the gels. Figure 7 shows a direct spot-to-spot comparison of the calculated RSD% values of both analysts for the pH range of 3.5–4.5. In this pH range, 22 spots were chosen. Spot number 1 represents the spot with the lowest spot intensity, and spot number 22 the spot with the highest spot intensity. The RSD% values of small spots detected in gels generated by the untrained analyst were always significantly higher. The spot intensity varies between the trained and untrained person, although the same method was performed. When exceeding a spot intensity of 1.5 (from spot no. 17), the differences of reproducibility are not very pronounced. However, only a few spots on the gels reach this high intensity. To confirm the different qualities of gels, an F-test was conducted. Therefore, the total variance of each group was calculated. Afterward, a statistical significant difference between the variances was checked via F-test. The hypotheses are made 1232

Journal of Proteome Research • Vol. 7, No. 3, 2008

H0: σ ˆ21

σ ˆ22

H1: σ ˆ21

σ ˆ22

σ ˆ21

as follows: is the estimated ; * , where ) variance of the trained person and σ ˆ22 the estimated variance of the untrained person. The test statistic F0 is calculated with the following formula: F0 )

σ ˆ22 σ ˆ21

, σ ˆ22 > σ ˆ21

The test statistic F0 is compared with the tabulated critical value Fcrit. If F0 > Fcrit, the null hypothesis H0 is abandoned and a significant difference is assumed. Unfortunately, the β-error cannot be controlled using this approach. The F-test takes the risk of an erroneous retention of the null hypothesis although the alternative hypothesis was correct. Table 3 shows the results of the F-test of the different pH groups. This investigation demonstrates a significant difference in the whole procedure accomplished by a trained or untrained person for all pH ranges excepting pH 5.5–6.5. In this case, the weakness of the F-test is represented: the β-error is usually rather high. Moreover, this error cannot be explicitly determined. Therefore, an existing difference often cannot be proven. Possibly, this holds true for the pH range 5.5–6.5 as well. Taken together, this analysis confirms the statement of Challapalli et al.16 that involving an untrained person in the performance of a gel electrophoresis procedure results in a lack of reproducibility.

4. Conclusion and Outlook The main error sources of variability in quantitative 2-DE and their contribution to total variability are summarized in Table 4. The major error sources include staining or rather detection of separated proteins, the transfer between the first and second dimension, and the experimenter’s skills on 2-DE technique. It is difficult to find the optimal conditions to stain the separated proteins and to destain the background sufficiently. Strong fluctuations of the baseline always complicate the detection of the true spot boundaries. Consequently, sensitivity and reproducibility become limited. Often, strong and irregular background signals result in complete failure. An improvement of the fluorescence detection was reached by repeating the entire staining procedure, but thereby the already long analysis time will be even more extended. Therefore, this cannot be an alternative for routine analysis. The possibility to detect proteins directly by native fluorescence offers many advantages compared to conventional staining methods. Both well-defined peaks and a 3-fold better signal-to-noise ratio at an 800-fold lower sample concentration resulted in a better precision of peak areas. The overall variance can be reduced by more than 1 order of magnitude using native fluorescence instead of conventional staining methods. Meanwhile, another improved protein detection alternative is available which is based on signal detection in the near-infrared range.38,39 Preliminary results using this sensitive detection method suggest a total error of just 5% RSD%.38 Own works in longer series39 seem to confirm these favorable findings for simple, one-dimensional separations. According to the law of error propagation, the major error sources dominate the total error. After isolating these major error sources, the precision in 2-DE will be improved, but it will still be worse than, for example, in HPLC or CE. Further minor sources of variability such as sample preparation, strip rehydration, protein loading, transfer between dimensions,

research articles

Quantitative Gel Electrophoresis/Sources of Variation Table 3. Results of F-Test with a Probability Value R ) 5% for the Different pH Ranges n

pH pH pH pH pH

3.5–4.5 4.5–5.5 5.5–6.5 6.5–7.5 7.5–9.0

23 35 21 22 13

F

0

2.486 32.722 1.084 3.855 4.815

Fcrit

F-test

2.048 1.772 2.124 2.084 2.687

F0 F0 F0 F0 F0

> > < > >

F F F F F

significant difference significant difference no significant difference significant difference significant difference

Table 4. Major and Minor Error Sources and Their Approximate Contribution to Total Variability in Quantitative 2D Gel Electrophoresis, Given as Percent RSDsa 15–70%15,17,18,40

total variability in quantitative 2-DE

major error sources 9 transfer between first and second dimension 9 visualization: Staining methods Native Fluorescence 9 analyst further minor error sources include sample preparation, IPG strip rehydration, protein loading, gel scanning, integration software, impact of the gel/interaction between gel, and separated proteins

10–15% [section 3.1] 13–70% [section 3.2] 12–16% [section 3.4] 10% [section 3.5]