unique peptides from 1484 proteins and demonstrated a dynamic range of

Unique peptides from 1484 proteins and demonstrated a

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unique peptides from 1,484 proteins and demonstrated a dynamic range of detection of 10,000. This method has been extended to comparative protein profiling by using in vivo N 14 /N 15 metabolic labeling[18,19] In Washburn et. al[18], S. cerevisiae was grown in both 14 N and 15 N minimal media and then 2,264 peptides and 872 proteins were uniquely identified. Also, accurate 14 N/ 15 N quantitation was determined for each peptide with an average standard deviation of 30%. C OMPARISON OF M RNA AND P ROTEIN L EVELS Even with these significant developments in the technologies used to quantify protein abundance over the past couple years, protein identification and quantification still lags behind the high throughput experimental techniques used to determine mRNA 4
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expression values. Yet, while mRNA expression values have shown their usefulness in a broad range of applications, including diagnosis and classification of cancers [20,21], these results are almost certainly only correlative, rather than causative; in the end it is, most probably, the concentration of proteins and their interactions that are the true causative forces in the cell, and it’s the corresponding protein quantities that we ought to be looking at. Primarily due to the limited ability to measure protein abundances, researchers have tried to find correlations between mRNA and protein expression in the hope that they could determine protein abundance levels from the more copious mRNA experiments. Alternatively, if there is definitively no correlation between mRNA and protein data, both quantities can be used as independent sources of information in machine learning algorithms. To date, there have been only a handful of efforts to find correlations between mRNA and protein expression levels, most notably in human cancers and yeast cells; for the most part, they have reported only minimal and limited correlations. One of the earliest analyses on correlation looked at 19 proteins in the human liver. Anderson et al[22] found a somewhat positive correlation of 0.48. Another limited analysis of three genes MMp-2, MNP-9 and TIMP-1 in human prostate cancers showed no significant relationship [23]. An additional cancer study [24] showed a significant correlation in only a small subset of the proteins studied . Conversely, Orntoft et al [25] found highly significant correlations in human carcinomas when looking at changes in mRNA and protein expression levels Protein and mRNA correlations in Yeast Many of the present efforts in correlating mRNA and protein expression have been conducted in yeast using two dimensional electrophoresis techniques, in particular: 2DE-1 : Gygi et al [7] found that even similar mRNA expression levels could have a wide range (up to 20 fold difference) of protein abundance levels and vice versa. 2DE-2: These results contrast with Futcher et al's [26] relatively high levels of correlations (r = 0.76) after transforming the data to normal distributions.
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