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Systematic analysis of protein pools, isoforms, and modifications affecting turnover and subcellular localization.

Ahmad Y, Boisvert FM, Lundberg E, Uhlen M, Lamond AI - Mol. Cell Proteomics (2011)

Bottom Line: Protein isoforms were also detected and their properties evaluated by fractionating cell extracts on one-dimensional SDS-PAGE prior to trypsin digestion and MS analysis and independently evaluating isotope ratio values for the same peptides isolated from different gel slices.The effect of protein phosphorylation on turnover rates was analyzed by comparing mean turnover values calculated for all peptides assigned to a protein, either including, or excluding, values for cognate phosphopeptides.Collectively, these experimental and analytical approaches provide a framework for expanding the functional annotation of the genome.

View Article: PubMed Central - PubMed

Affiliation: Wellcome Trust Centre for Gene Regulation and Expression, College of Life Sciences, University of Dundee, Dundee DD1 5EH United Kingdom.

ABSTRACT
In higher eukaryotes many genes encode protein isoforms whose properties and biological roles are often poorly characterized. Here we describe systematic approaches for detection of either distinct isoforms, or separate pools of the same isoform, with differential biological properties. Using information from ion intensities we have estimated protein abundance levels and using rates of change in stable isotope labeling with amino acids in cell culture isotope ratios we measured turnover rates and subcellular distribution for the HeLa cell proteome. Protein isoforms were detected using three data analysis strategies that evaluate differences between stable isotope labeling with amino acids in cell culture isotope ratios for specific groups of peptides within the total set of peptides assigned to a protein. The candidate approach compares stable isotope labeling with amino acids in cell culture isotope ratios for predicted isoform-specific peptides, with ratio values for peptides shared by all the isoforms. The rule of thirds approach compares the mean isotope ratio values for all peptides in each of three equal segments along the linear length of the protein, assessing differences between segment values. The three in a row approach compares mean isotope ratio values for each sequential group of three adjacent peptides, assessing differences with the mean value for all peptides assigned to the protein. Protein isoforms were also detected and their properties evaluated by fractionating cell extracts on one-dimensional SDS-PAGE prior to trypsin digestion and MS analysis and independently evaluating isotope ratio values for the same peptides isolated from different gel slices. The effect of protein phosphorylation on turnover rates was analyzed by comparing mean turnover values calculated for all peptides assigned to a protein, either including, or excluding, values for cognate phosphopeptides. Collectively, these experimental and analytical approaches provide a framework for expanding the functional annotation of the genome.

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Alternative splicing leading to protein isoforms.A, A single gene can encode multiple proteins because of alternative splicing. After transcription of a gene, exons of the resultant RNA can be reconnected in multiple ways during RNA splicing, resulting in the translation of protein isoforms, with red and green areas signifying differences between the isoforms. B, Protein isoforms represent several different forms of a protein and have a largely shared sequence, however small differences occur. Mass spectrometery can be used to identify both common peptides shared by all isoforms and specific peptides (shown in red and green) that are unique to each isoform. C, Using these identified peptides it is possible to extract abundance, localization, and turnover information for a protein by using either shared peptides or isoform specific peptides.
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Figure 1: Alternative splicing leading to protein isoforms.A, A single gene can encode multiple proteins because of alternative splicing. After transcription of a gene, exons of the resultant RNA can be reconnected in multiple ways during RNA splicing, resulting in the translation of protein isoforms, with red and green areas signifying differences between the isoforms. B, Protein isoforms represent several different forms of a protein and have a largely shared sequence, however small differences occur. Mass spectrometery can be used to identify both common peptides shared by all isoforms and specific peptides (shown in red and green) that are unique to each isoform. C, Using these identified peptides it is possible to extract abundance, localization, and turnover information for a protein by using either shared peptides or isoform specific peptides.

Mentions: We have analyzed HeLa cell SILAC data describing global protein abundance, localization, and turnover (33), using three approaches to detect protein isoforms that have differential properties (Fig. 1). First, a candidate approach was used. For genes encoding known isoforms, average intensity values were compared for peptides shared between all isoforms with candidate, isoform-specific peptides (Fig. 2). This is illustrated for the NudCD1 protein, which has three reported isoforms (39). Using average values for all peptides detected that are common to the three isoforms (blue), there is similar average peptide intensity in the cytoplasm and nucleus, with little signal in the nucleolus. However, although analysis of a peptide predicted to be specific to isoform 3 showed intensity in both cytoplasmic and nuclear compartments (green, ∼3:2 cytoplasmic/nuclear), a peptide predicted to be specific for isoform 2 (red), instead showed exclusively cytoplasmic signal (Fig. 2A). We were unable to detect reliably any peptides that were unique to isoform 1. However, as there is strong overall peptide signal in the nucleus that cannot be accounted for by the intensities of either the isoform 2, or isoform 3-specific peptides, we infer that isoform 1 is likely to be enriched in the nucleus.


Systematic analysis of protein pools, isoforms, and modifications affecting turnover and subcellular localization.

Ahmad Y, Boisvert FM, Lundberg E, Uhlen M, Lamond AI - Mol. Cell Proteomics (2011)

Alternative splicing leading to protein isoforms.A, A single gene can encode multiple proteins because of alternative splicing. After transcription of a gene, exons of the resultant RNA can be reconnected in multiple ways during RNA splicing, resulting in the translation of protein isoforms, with red and green areas signifying differences between the isoforms. B, Protein isoforms represent several different forms of a protein and have a largely shared sequence, however small differences occur. Mass spectrometery can be used to identify both common peptides shared by all isoforms and specific peptides (shown in red and green) that are unique to each isoform. C, Using these identified peptides it is possible to extract abundance, localization, and turnover information for a protein by using either shared peptides or isoform specific peptides.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3316725&req=5

Figure 1: Alternative splicing leading to protein isoforms.A, A single gene can encode multiple proteins because of alternative splicing. After transcription of a gene, exons of the resultant RNA can be reconnected in multiple ways during RNA splicing, resulting in the translation of protein isoforms, with red and green areas signifying differences between the isoforms. B, Protein isoforms represent several different forms of a protein and have a largely shared sequence, however small differences occur. Mass spectrometery can be used to identify both common peptides shared by all isoforms and specific peptides (shown in red and green) that are unique to each isoform. C, Using these identified peptides it is possible to extract abundance, localization, and turnover information for a protein by using either shared peptides or isoform specific peptides.
Mentions: We have analyzed HeLa cell SILAC data describing global protein abundance, localization, and turnover (33), using three approaches to detect protein isoforms that have differential properties (Fig. 1). First, a candidate approach was used. For genes encoding known isoforms, average intensity values were compared for peptides shared between all isoforms with candidate, isoform-specific peptides (Fig. 2). This is illustrated for the NudCD1 protein, which has three reported isoforms (39). Using average values for all peptides detected that are common to the three isoforms (blue), there is similar average peptide intensity in the cytoplasm and nucleus, with little signal in the nucleolus. However, although analysis of a peptide predicted to be specific to isoform 3 showed intensity in both cytoplasmic and nuclear compartments (green, ∼3:2 cytoplasmic/nuclear), a peptide predicted to be specific for isoform 2 (red), instead showed exclusively cytoplasmic signal (Fig. 2A). We were unable to detect reliably any peptides that were unique to isoform 1. However, as there is strong overall peptide signal in the nucleus that cannot be accounted for by the intensities of either the isoform 2, or isoform 3-specific peptides, we infer that isoform 1 is likely to be enriched in the nucleus.

Bottom Line: Protein isoforms were also detected and their properties evaluated by fractionating cell extracts on one-dimensional SDS-PAGE prior to trypsin digestion and MS analysis and independently evaluating isotope ratio values for the same peptides isolated from different gel slices.The effect of protein phosphorylation on turnover rates was analyzed by comparing mean turnover values calculated for all peptides assigned to a protein, either including, or excluding, values for cognate phosphopeptides.Collectively, these experimental and analytical approaches provide a framework for expanding the functional annotation of the genome.

View Article: PubMed Central - PubMed

Affiliation: Wellcome Trust Centre for Gene Regulation and Expression, College of Life Sciences, University of Dundee, Dundee DD1 5EH United Kingdom.

ABSTRACT
In higher eukaryotes many genes encode protein isoforms whose properties and biological roles are often poorly characterized. Here we describe systematic approaches for detection of either distinct isoforms, or separate pools of the same isoform, with differential biological properties. Using information from ion intensities we have estimated protein abundance levels and using rates of change in stable isotope labeling with amino acids in cell culture isotope ratios we measured turnover rates and subcellular distribution for the HeLa cell proteome. Protein isoforms were detected using three data analysis strategies that evaluate differences between stable isotope labeling with amino acids in cell culture isotope ratios for specific groups of peptides within the total set of peptides assigned to a protein. The candidate approach compares stable isotope labeling with amino acids in cell culture isotope ratios for predicted isoform-specific peptides, with ratio values for peptides shared by all the isoforms. The rule of thirds approach compares the mean isotope ratio values for all peptides in each of three equal segments along the linear length of the protein, assessing differences between segment values. The three in a row approach compares mean isotope ratio values for each sequential group of three adjacent peptides, assessing differences with the mean value for all peptides assigned to the protein. Protein isoforms were also detected and their properties evaluated by fractionating cell extracts on one-dimensional SDS-PAGE prior to trypsin digestion and MS analysis and independently evaluating isotope ratio values for the same peptides isolated from different gel slices. The effect of protein phosphorylation on turnover rates was analyzed by comparing mean turnover values calculated for all peptides assigned to a protein, either including, or excluding, values for cognate phosphopeptides. Collectively, these experimental and analytical approaches provide a framework for expanding the functional annotation of the genome.

Show MeSH