Protein abundances, quantitative

Zappacosta, F., and Annan, R.S. (2004) N-terminal isotope tagging strategy for quantitative proteomics Results-driven analysis of protein abundance changes. Anal. Chem. 76, 6618-6627. 

Various quantitative and statistical validation processes have been described, accounting for the fact that SpCs tend to be small numbers and vary due to the partial stochasticity of the process. In the example datasets included in this chapter, the relationship between the SpC and protein abundance obtained experimentally is shown in Figure 2, demonstrating that many proteins in bacterial cells are low in abundance while a small subset are highly abundant. Several studies have compared label-free with labeling methods or assessed its statistical validity (93-95). Overall, SpC alone should not be used as a means for absolute quantification (92,96), but it is quite adequate for... 

Estimates of protein abundance have been linked to codon bias, and the completion of the yeast genome sequence has enabled protein spot abundance to be coupled with quantitative transcript-based analyses. 

A major limitation to the capacity of 2-DE to display complete proteomes is the veiy high dynamic range of protein abundance, estimated at 10 for cells and tissues (Corthals et al., 2000) and 10 for plasma (Anderson and Anderson, 2002). This is beyond the dynamic range of 2-DE, with an estimated maximum dynamic range of 10" (Rabilloud, 2002). Clearly, the development of reliable and reproducible prefractionation strategies will be essential to access and retrieve quantitative data for the less abundant proteins present in biological samples such as the heart. 

In addition to protein identification and characterization, another major goal of proteomics research is to quantify protein expression levels. However, MS is not inherently quantitative. Thus, the intensity of a peptide ion introduced to the mass spectrometer via ESI or MALDI does not reflect necessarily the amount of peptide present in the sample, due to the strong dependence of ionization on the physical and chemical nature of the analyte. To overcome this challenge, numerous quantitative analysis strategies have been developed to measure the differences in protein abundances between two different cellular states of a biological system (for example, normal and diseased cells). 

Proteomic analysis frequently involves comparison of protein levels in experimental and control samples, which is linked with the quantitative analysis (see Chapter 8). In some cases, it is necessary to follow protein abundances over time. Changes in protein levels in cells or biofluids may be monitored over a few hours or days, which does not put much pressure on the temporal resolution of the analytical procedure [at least not to the extent observed in ultrafast time-resolved mass spectrometry (TRMS) studies introduced in other chapters of this book]. LC-MS is a simple approach to obtain relative abundances of proteins in highly complex samples [30]. It is possible to carry out quantitative comparisons... 

In order to profile proteins in the sample to confirm that changes occur in carbonylation stoichiometry rather than in the protein abundance. Scaffold allows for simultaneous comparison of multiple proteomic data sets in which the list of identified proteins can be sorted by various parameters. The spectral counting technique for relative protein quantitation utilizes the total number of MS/MS spectra identified for a particular protein as a measure of protein abundance, and consequently this parameter can be used to classify the abundance. Published protocols [14,15] can be used as methods for relative quantitation in which the change in abundance can be determined by the ratios as follows ... 

Spectral Count The total number of MS/MS spectra (usually corresponding to redundant and nonre-dundant peptides) used for identification of proteins. Spectral count increases with protein abundance, hence spectral counting is a useful approach in assessing relative protein abundance by a label-free quantitative strategy. 

In contrast, when using fluorescence immunocytochemistry to label proteins in tissue sections, the absolute relationship of fluorescence intensity to protein abundance can only be determined through conducting rigorous control experiments, and thus linearity should not be presumed. With that said, because CCD and photomultipHer tube detection systems are linear across a broad range of fluorescence intensities [36], quantitative fluorescence microscopy has been used in numerous smdies to measure relative changes in protein level [33, 35, 36]. In a system where the expression of a protein is only effected in a subpopulation of cells (e.g., GAD67 expression is reduced in a subset of PV+ interneurons in schizophrenia—see ref. 45), quantitative fluorescence immunohistochemistry will be more informative than techniques (e.g.. Western blot) that treat the tissue as a whole. 

The feasibility of this approach to not only differentiate pathogenic and nonpathogenic strains of bacteria based on significant differences in protein mass but also on the basis of variations in levels of protein expression was demonstrated using a method for quantitating protein expression by LC/MS of whole proteins.54 This method is based on the fact that some proteins present in cells are abundant universal proteins whose expression levels exhibit little variation. This method demonstrates that these co-extracted proteins can be used as internal standards to which the other proteins in the sample can be compared. By comparing the intensities of a selected protein to a marker protein, or internal standard, a relative ratio is obtained. This ratio... 

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