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Introduction in verification of protein coding transcripts in the newt N.v. using a SILAC driven mass spectrometry approach

Lack of sequence information has greatly impeded analysis of biological processes and identification of proteins in several non-standard model organisms for which no comprehensive genome characterization is available. Even if nucleotide sequence data (i.e. EST libraries) is available, it is often difficult to use these data for identification of new proteins, particularly if EST clones lack obvious homologues in other species. Furthermore, it is often difficult to distinguish open reading frames in EST clones lacking obvious homologues from 3'-UTRs, intermediate splice products or cloning artifacts.

Traditional database searches usually allow only identification of peptides that are conserved in newly detected proteins and putative homologous proteins from closely related species. Unfortunately, such an approach is not efficient to recognize proteins that are phylogenetically distant from available reference organisms, or belong to poorly conserved protein families. The NCBI databases hosts only 131 protein and 114 nucleotide entries (as of March 2009), which represent less than 100 unique protein sequences due to redundant information. This paucity is even more dramatic in the light of the size of the newt genome, which is approximately 10-times larger than the human genome.

Our approach is derived from the SILAC method (Stable Isotope Labeling with Amino acids in Cell culture) and uses biologically produced 13C6-lysine containing proteins to label newly synthesized proteins in regenerating newt appendages in vivo. We took advantage of so called “pulsed or dynamic” SILAC approach which has already been used to determine translation rates or protein turnover in human cancer cell lines in vitro. Mass spectrometric analysis of mixed samples from labeled and unlabeled tissue enabled us to detect a large number of proteinsthat were incorporated into regenerating newt tails. The recognition of SILAC-peptide pairs significantly improved the rate of protein identification.

Here we present 15169 peptides which were identified by our in vivo SILAC approach using the EST database.

Mol Cell Proteomics. 2010 Jun;9(6):1157-66. Epub 2010 Feb 5.
Advanced identification of proteins in uncharacterized proteomes by pulsed in vivo stable isotope
labeling-based mass spectrometry.
Looso M, Borchardt T, Krueger M, Braun T.