Attempts to correlate protein abundance with mRNA expression levels have had variable success. We review the results of these comparisons, focusing on yeast. In the process, we survey experimental techniques for determining protein abundance, principally two-dimensional gel electrophoresis and mass-spectrometry. We also merge many of the available yeast protein-abundance datasets, using the resulting larger 'meta-dataset' to find correlations between protein and mRNA expression, both globally and within smaller categories.

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Comparing protein abundance and mRNA expression levels on a genomic scale

Two-dimensional (2D) gel electrophoresis is a powerful technique enabling simultaneous visualization of relatively large portions of the proteome. However, the well documented issues of variation and lack of sensitivity and quantitative capabilities of existing labeling reagents, has limited the use of this technique as a quantitative tool. Two-dimensional difference gel electrophoresis (2D DIGE) builds on this technique by adding a highly accurate quantitative dimension. 2D DIGE enables multiple protein extracts to be separated on the same 2D gel. This is made possible by labeling of each extract using spectrally resolvable, size and charge-matched fluorescent dyes known as CyDye DIGE fluors. 2D DIGE involves use of a reference sample, known as an internal standard, which comprises equal amounts of all biological samples in the experiment. Including the internal standard on each gel in the experiment with the individual biological samples means that the abundance of each protein spot on a gel can be measured relative (i.e. as a ratio) to its corresponding spot in the internal standard present on the same gel. Ettan DIGE is the system of technologies that has been optimized to fully benefit from the advantages provided by 2D DIGE.

The development of the DIGE system: 2D fluorescence difference gel analysis technology.

https://aasldpubs.onlinelibrary.wiley.com/doi/epdf/10.1002/hep.22580

Molecular mechanisms of hepatocellular carcinoma.

Addressing Accuracy and Precision Issues in iTRAQ Quantitation

iTRAQ (isobaric tags for relative or absolute quantitation) is a mass spectrometry technology that allows quantitative comparison of protein abundance by measuring peak intensities of reporter ions released from iTRAQ-tagged peptides by fragmentation during MS/MS. However, current data analysis techniques for iTRAQ struggle to report reliable relative protein abundance estimates and suffer with problems of precision and accuracy. The precision of the data is affected by variance heterogeneity: low signal data have higher relative variability; however, low abundance peptides dominate data sets. Accuracy is compromised as ratios are compressed toward 1, leading to underestimation of the ratio. This study investigated both issues and proposed a methodology that combines the peptide measurements to give a robust protein estimate even when the data for the protein are sparse or at low intensity. Our data indicated that ratio compression arises from contamination during precursor ion selection, which occurs at a consistent proportion within an experiment and thus results in a linear relationship between expected and observed ratios. We proposed that a correction factor can be calculated from spiked proteins at known ratios. Then we demonstrated that variance heterogeneity is present in iTRAQ data sets irrespective of the analytical packages, LC-MS/MS instrumentation, and iTRAQ labeling kit (4-plex or 8-plex) used. We proposed using an additive-multiplicative error model for peak intensities in MS/MS quantitation and demonstrated that a variance-stabilizing normalization is able to address the error structure and stabilize the variance across the entire intensity range. The resulting uniform variance structure simplifies the downstream analysis. Heterogeneity of variance consistent with an additive-multiplicative model has been reported in other MS-based quantitation including fields outside of proteomics; consequently the variance-stabilizing normalization methodology has the potential to increase the capabilities of MS in quantitation across diverse areas of biology and chemistry.

Addressing accuracy and precision issues in iTRAQ quantitation

Separation and relative quantitation of complex protein mixtures remain two of the most challenging aspects of proteomics. Here an advanced technique called fluorescence difference 2-D gel electrophoresis technology (2D-DIGE) has been applied to a model system study of the Escherichia coli proteome after benzoic acid treatment. The molecular weight and charge matched cyanine dyes enable pre-electrophoretic labelling of control and treated samples which are then mixed and run in the same gel. Pooled control and treated samples labelled with Cy trade mark 3 were used as an internal standard for both Cy5 labelled control and treated E. coli samples. Together with DeCyder trade mark imaging analysis software, more accurate quantitative analysis than conventional two-dimensional polyacrylamide gel electrophoresis was achieved. Using matrix-assisted laser desorption/ionization-time of flight and quadrupole-time of flight mass spectrometry a total of 179 differentially expressed protein spots were identified. These included enzymes, stress related and substrate (e.g. amino acids, maltose, ribose and TRP repressor) binding proteins. Of the spots analysed, 77% contained only one protein species per spot, hence the change in protein expression measured was solely attributed to the identified protein. Many membrane proteins and protein isoforms were identified indicating both adequate solubilization of E. coli samples and potential post-translational modification. The results indicate that the regulatory mechanisms following benzoic acid treatment of E. coli are far more complicated than hitherto expected.

Jun X. Yan

Papers

Fluorescence two-dimensional difference gel electrophoresis and mass spectrometry based proteomic analysis of Escherichia coli.