We describe a protein quantification method that exploits the subtle mass differences caused by neutron-binding energy variation in stable isotopes. These mass differences are synthetically encoded into amino acids and incorporated into yeast and mouse proteins with metabolic labeling; analysis with high mass resolution (>100,000) reveals the isotopologue-embedded peptide signals permitting quantification. We conclude neutron encoding will enable high levels of multi-plexing (> 10) with high dynamic range and accuracy.
Stressed cells coordinate a multi-faceted response spanning many levels of physiology. Yet knowledge of the complete stress-activated regulatory network as well as design principles for signal integration remains incomplete. We developed an experimental and computational approach to integrate available protein interaction data with gene fitness contributions, mutant transcriptome profiles, and phospho-proteome changes in cells responding to salt stress, to infer the salt-responsive signaling network in yeast. The inferred subnetwork presented many novel predictions by implicating new regulators, uncovering unrecognized crosstalk between known pathways, and pointing to previously unknown ‘hubs’ of signal integration. We exploited these predictions to show that Cdc14 phosphatase is a central hub in the network and that modification of RNA polymerase II coordinates induction of stress-defense genes with reduction of growth-related transcripts. We find that the orthologous human network is enriched for cancer-causing genes, underscoring the importance of the subnetwork's predictions in understanding stress biology.
We describe a synthesis strategy for the preparation of lysine isotopologues that differ in mass by as little as 6 mDa. We demonstrate that incorporation of these molecules into the proteomes of actively growing cells does not affect cellular proliferation, and we discuss how to use the embedded mass signatures (neutron encoding (NeuCode)) for multiplexed proteome quantification by means of high-resolution mass spectrometry. NeuCode SILAC amalgamates the quantitative accuracy of SILAC with the multiplexing of isobaric tags and, in doing so, offers up new opportunities for biological investigation. Large-scale technologies for the comparative analysis of proteomes have become essential for modern biology and medicine (1, 2). To satisfy this increasing demand and boost statistical power, parallel processing of proteomes (i.e. multiplexing) is key. The ground was broken in this field about two decades ago by advances in both MS and stable isotope labeling (3-5). Since then, two distinct strategies have emerged, each with its own strengths and weaknesses. The first approach, stable isotope labeling by amino acids in cell culture (SILAC), 1 metabolically incorporates labeled amino acids into proteins and is considered the gold standard (6 -8). SILAC quantification provides unmatched accuracy, but simultaneous comparison of more than three proteomes, although possible, is not practical for most global studies (9, 10). A second, and increasingly popular, method is to chemically modify peptides originating from up to 10 different sources (a 3-to 5-fold boost in throughput over SILAC) with isobaric reagents (e.g. TMT or iTRAQ) (11)(12)(13)(14). The escalated throughput afforded by this strategy is, for many applications, essential; however, multiplexing via isobaric tagging comes at the cost of quantitative accuracy (15-17). Furthermore, because each sample is handled independently prior to labeling, systematic and random variation that occurs during sample processing cannot be accounted for as it is with metabolic labeling. Thus, experimenters designing a quantitative proteomics experiment must choose between accuracy and throughput.Recently we described a new approach that blends the SILAC and isobaric tagging methods (18). The strategy, neutron encoding (NeuCode), relies on the mass defects of atoms and their isotopes (19). In studies using two isotopologues of lysine, differing by 36 mDa, NeuCode SILAC quantified proteins as well as traditional SILAC, but it allowed deeper proteome coverage. NeuCode harnesses the exceptional resolving power of modern FT-MS systems so that quantitative information is only revealed by high-resolution scanning when desired, in either MS or tandem MS scans (20,21).Owing to the lack of suitable lysine isotopologues, our initial work with NeuCode SILAC offered only duplex quantification; consequently, we could only predict the utility of NeuCode SILAC (18). To test our supposition that NeuCode SILAC has the potential to combine the benefits of traditional SILAC and
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