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Comparative proteomic analysis of eleven common cell lines reveals ubiquitous but varying expression of most proteins.

Geiger T, Wehner A, Schaab C, Cox J, Mann M - Mol. Cell Proteomics (2012)

Bottom Line: Despite the distinct origins of the cell lines, our quantitative results showed surprisingly high similarity in terms of expressed proteins.Nevertheless, this global similarity of the proteomes did not imply equal expression levels of individual proteins across the 11 cell lines, as we found significant differences in expression levels for an estimated two-third of them.MCP 2012, PMID: 22301388) (17) these data can be used to obtain reference expression profiles for proteins of interest both within and across cell line proteomes.

View Article: PubMed Central - PubMed

Affiliation: Department of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany.

ABSTRACT
Deep proteomic analysis of mammalian cell lines would yield an inventory of the building blocks of the most commonly used systems in biological research. Mass spectrometry-based proteomics can identify and quantify proteins in a global and unbiased manner and can highlight the cellular processes that are altered between such systems. We analyzed 11 human cell lines using an LTQ-Orbitrap family mass spectrometer with a "high field" Orbitrap mass analyzer with improved resolution and sequencing speed. We identified a total of 11,731 proteins, and on average 10,361 ± 120 proteins in each cell line. This very high proteome coverage enabled analysis of a broad range of processes and functions. Despite the distinct origins of the cell lines, our quantitative results showed surprisingly high similarity in terms of expressed proteins. Nevertheless, this global similarity of the proteomes did not imply equal expression levels of individual proteins across the 11 cell lines, as we found significant differences in expression levels for an estimated two-third of them. The variability in cellular expression levels was similar for low and high abundance proteins, and even many of the most highly expressed proteins with household roles showed significant differences between cells. Metabolic pathways, which have high redundancy, exhibited variable expression, whereas basic cellular functions such as the basal transcription machinery varied much less. We harness knowledge of these cell line proteomes for the construction of a broad coverage "super-SILAC" quantification standard. Together with the accompanying paper (Schaab, C. MCP 2012, PMID: 22301388) (17) these data can be used to obtain reference expression profiles for proteins of interest both within and across cell line proteomes.

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Related in: MedlinePlus

Use of cell lines as a spike-in SILAC standard. Knowledge of the overall similarities of the proteomes was used to construct a five cell line, heavy labeled “super-SILAC” reference standard. A, HeLa and K562 as well as Jurkat and K562 (B) proteins are sufficiently similar that most of the SILAC ratios are within a fivefold ratio above and below the one to one ratio. C, Quantification of the heavy super-SILAC mix consisting of five cell lines quantifies 96% of the K562 proteome within a fivefold ratio.
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Figure 6: Use of cell lines as a spike-in SILAC standard. Knowledge of the overall similarities of the proteomes was used to construct a five cell line, heavy labeled “super-SILAC” reference standard. A, HeLa and K562 as well as Jurkat and K562 (B) proteins are sufficiently similar that most of the SILAC ratios are within a fivefold ratio above and below the one to one ratio. C, Quantification of the heavy super-SILAC mix consisting of five cell lines quantifies 96% of the K562 proteome within a fivefold ratio.

Mentions: As expected from the high correlations, even the SILAC quantification experiments between binary combinations of heavy and light labeled cell lines resulted in narrow ratio distributions (Fig. 6A, 6B). This was further improved in the quantification of the heavy super-SILAC mix against a single cell line (Fig. 6C). These experiments also suggest a general strategy to construct super-SILAC mixes and to evaluate their suitability for quantifying any cell line (or tissue) of interest. Importantly, this only involves label free quantification of the various cell lines that are suggested for the super-SILAC mix (heavy or light) against the label-free proteome of interest.


Comparative proteomic analysis of eleven common cell lines reveals ubiquitous but varying expression of most proteins.

Geiger T, Wehner A, Schaab C, Cox J, Mann M - Mol. Cell Proteomics (2012)

Use of cell lines as a spike-in SILAC standard. Knowledge of the overall similarities of the proteomes was used to construct a five cell line, heavy labeled “super-SILAC” reference standard. A, HeLa and K562 as well as Jurkat and K562 (B) proteins are sufficiently similar that most of the SILAC ratios are within a fivefold ratio above and below the one to one ratio. C, Quantification of the heavy super-SILAC mix consisting of five cell lines quantifies 96% of the K562 proteome within a fivefold ratio.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3316730&req=5

Figure 6: Use of cell lines as a spike-in SILAC standard. Knowledge of the overall similarities of the proteomes was used to construct a five cell line, heavy labeled “super-SILAC” reference standard. A, HeLa and K562 as well as Jurkat and K562 (B) proteins are sufficiently similar that most of the SILAC ratios are within a fivefold ratio above and below the one to one ratio. C, Quantification of the heavy super-SILAC mix consisting of five cell lines quantifies 96% of the K562 proteome within a fivefold ratio.
Mentions: As expected from the high correlations, even the SILAC quantification experiments between binary combinations of heavy and light labeled cell lines resulted in narrow ratio distributions (Fig. 6A, 6B). This was further improved in the quantification of the heavy super-SILAC mix against a single cell line (Fig. 6C). These experiments also suggest a general strategy to construct super-SILAC mixes and to evaluate their suitability for quantifying any cell line (or tissue) of interest. Importantly, this only involves label free quantification of the various cell lines that are suggested for the super-SILAC mix (heavy or light) against the label-free proteome of interest.

Bottom Line: Despite the distinct origins of the cell lines, our quantitative results showed surprisingly high similarity in terms of expressed proteins.Nevertheless, this global similarity of the proteomes did not imply equal expression levels of individual proteins across the 11 cell lines, as we found significant differences in expression levels for an estimated two-third of them.MCP 2012, PMID: 22301388) (17) these data can be used to obtain reference expression profiles for proteins of interest both within and across cell line proteomes.

View Article: PubMed Central - PubMed

Affiliation: Department of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany.

ABSTRACT
Deep proteomic analysis of mammalian cell lines would yield an inventory of the building blocks of the most commonly used systems in biological research. Mass spectrometry-based proteomics can identify and quantify proteins in a global and unbiased manner and can highlight the cellular processes that are altered between such systems. We analyzed 11 human cell lines using an LTQ-Orbitrap family mass spectrometer with a "high field" Orbitrap mass analyzer with improved resolution and sequencing speed. We identified a total of 11,731 proteins, and on average 10,361 ± 120 proteins in each cell line. This very high proteome coverage enabled analysis of a broad range of processes and functions. Despite the distinct origins of the cell lines, our quantitative results showed surprisingly high similarity in terms of expressed proteins. Nevertheless, this global similarity of the proteomes did not imply equal expression levels of individual proteins across the 11 cell lines, as we found significant differences in expression levels for an estimated two-third of them. The variability in cellular expression levels was similar for low and high abundance proteins, and even many of the most highly expressed proteins with household roles showed significant differences between cells. Metabolic pathways, which have high redundancy, exhibited variable expression, whereas basic cellular functions such as the basal transcription machinery varied much less. We harness knowledge of these cell line proteomes for the construction of a broad coverage "super-SILAC" quantification standard. Together with the accompanying paper (Schaab, C. MCP 2012, PMID: 22301388) (17) these data can be used to obtain reference expression profiles for proteins of interest both within and across cell line proteomes.

Show MeSH
Related in: MedlinePlus