Protein identification pipeline for the homology-driven proteomics

Junqueira, Magno; Spirin, Victor; Balbuena, Tiago Santana; Thomas, Heidi; Adzhubei, Ivan; Sunyaev, Shamil; Shevchenko, Andrej

doi:10.1016/j.jprot.2008.07.003

Cited by 77 publications

(71 citation statements)

References 35 publications

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“…Such multi-pass approaches, in contrast to multi-search analyses, reduce the number of false negatives while not significantly increasing the overall runtime [108]. Therefore it can be expected that de novo sequencing will, increasingly, find its way into computational pipelines for MS data analysis, as exemplified in a study by Junqueira and colleagues [109], in the near future. It has long been recognized in proteomics that standards and standard datasets need to be available for benchmarking of the current state of the art and new methods [110].…”

Section: Discussionmentioning

confidence: 99%

Algorithms for thede novosequencing of peptides from tandem mass spectra

Allmer¹

2011

Expert Review of Proteomics

107

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Proteomics is the study of the proteins, their time and location dependent expression profiles as well as their modifications and interactions. Mass spectrometry is useful to investigate many of the questions asked in proteomics. Typically database search methods are employed to identify proteins from complex mixtures. However, often databases are not available or despite their availability some sequences are not readily found therein. To overcome this problem de novo sequencing can be used to directly assign a peptide sequence to an MS/MS spectrum. Many algorithms have been proposed for de novo sequencing and a selection of them is detailed in this review. Although a standard accuracy measure has not been agreed upon in the field, relative algorithm performance is discussed. The current state of the de novo sequencing is assessed thereafter and finally, examples are used to construct possible future perspectives of the field. Running title:De novo sequencing of MS/MS spectra

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Section: Discussionmentioning

confidence: 99%

Algorithms for thede novosequencing of peptides from tandem mass spectra

Allmer¹

2011

Expert Review of Proteomics

107

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“…Unfortunately, genome sequencing is still a relatively new approach and is still fairly expensive therefore most plant species of interest have not yet been sequenced, with consequent gaps in the databases. In such cases, it is possible to exploit the homology-driven proteomics for the characterization of proteomes (Junqueira et al, 2008). The availability of fairly large databases of genomic data from model systems has made it feasible to explore the proteomics of single cell types isolated from complex tissues through a procedure known as laser microdissection.…”

Section: Problems With Proteomic Analysesmentioning

confidence: 99%

Proteomic Analyses of Cells Isolated by Laser Microdissection

Fiorilli¹,

Klink²,

Balestrini³

2012

Integrative Proteomics

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“…4 and supplemental Table 8). The identification of new proteins from organisms with unknown genomes has already been demonstrated for unlabeled peptides by filtering peptide spectra against a non-annotated library of background spectra and automated de novo interpretation by specific algorithms followed by MS BLAST (3,4,18).…”

Section: Detection Of Silac Peptide Pairs Permits Characterization Ofmentioning

confidence: 99%

“…Most of these techniques are based on filtering of spectra from unlabeled peptides against a non-annotated library of background spectra and automated de novo interpretation by software methods followed by MS BLAST (4,18).…”

Section: G G C C a T T A C G G C C G G G G A G A C G T G T C C T G T mentioning

confidence: 99%

“…1 and 2). Traditional database searches usually allow only identification of peptides that are conserved in newly detected proteins and putative homologous proteins from closely related species (3,4). 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.…”

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Advanced Identification of Proteins in Uncharacterized Proteomes by Pulsed in Vivo Stable Isotope Labeling-based Mass Spectrometry

Looso

Borchardt

Krüger

et al. 2010

Molecular & Cellular Proteomics

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Despite progress in the characterization of their genomes, proteomes of several model organisms are often only poorly characterized. This problem is aggravated by the presence of large numbers of expressed sequence tag clones that lack homologues in other species, which makes it difficult to identify new proteins irrespective of whether such molecules are involved in species-specific biological processes. We have used a pulsed stable isotope labeling with amino acids in cell culture (SILAC)-based mass spectrometry method, which is based on the detection of paired peptides after [ 13 C 6 ]lysine incorporation into proteins in vivo, to greatly increase the confidence of protein identification in cross-species database searches. The method was applied to identify nearly 3000 proteins in regenerating tails of the urodele amphibian Notophthalmus viridescens, which possesses outstanding capabilities in the regeneration of complex tissues. We reason that pulsed in vivo SILAC represents a versatile tool to identify new proteins in species for which only limited sequence information exists. Molecular & Cellular Proteomics 9:1157-1166, 2010.Lack of sequence information has greatly impeded analysis of biological processes and identification of proteins in several nonstandard model organisms for which no comprehensive genome characterization is available. Even if nucleotide sequence data (i.e. EST libraries) are 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 3Ј-untranslated regions, intermediate splice products, or cloning artifacts. In addition, several other problems aggravate identification of peptides in partially characterized genomes, which spurred the development of a number of alternative approaches (reviewed in Refs. 1 and 2). Traditional database searches usually allow only identification of peptides that are conserved in newly detected proteins and putative homologous proteins from closely related species (3, 4). 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 reliable identification of unknown proteins in "isolated" model organisms currently remains unsolved, although new software tools based on MS BLAST sequencesimilarity searches that use multiple redundant and partially accurate candidate peptide sequences have been developed to cope with this difficulty. One potential solution for this problem is de novo protein sequencing, which, however, remains a challenging problem (reviewed in Refs. 5 and 6).The urodele amphibian Notophthalmus viridescens, vulgo newts, which is one of the best-characterized organisms for the regeneration of complex tissues, is an example of an "isolated" model organism. Newts are able to completely regenerate limbs (7) and ...

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Protein identification pipeline for the homology-driven proteomics

Cited by 77 publications

References 35 publications

Algorithms for thede novosequencing of peptides from tandem mass spectra

Algorithms for thede novosequencing of peptides from tandem mass spectra

Proteomic Analyses of Cells Isolated by Laser Microdissection

Advanced Identification of Proteins in Uncharacterized Proteomes by Pulsed in Vivo Stable Isotope Labeling-based Mass Spectrometry

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