Deep proteome and transcriptome mapping of a human cancer cell line

Nagaraj, Nagarjuna; Wiśniewski, Jacek R.; Geiger, Tamar; Cox, Juergen; Kircher, Martin; Kelso, Janet; Pääbo, Svante; Mann, Matthias

doi:10.1038/msb.2011.81

Cited by 936 publications

(950 citation statements)

References 35 publications

Supporting

Mentioning

862

Contrasting

Unclassified

Order By: Relevance

“…These values are in good agreement with estimates reported in previous large‐scale proteomics studies (Nagaraj et al , 2011; Kulak et al , 2014; Hein et al , 2015), and this adds confidence to our use of γ‐tubulin data for calibration purposes. Also, we emphasize that although this calibration is critical for calculations of exact absolute copy numbers, any future correction of γ‐tubulin abundance would not affect relative numbers or any of the major conclusions.…”

Section: Discussionsupporting

confidence: 90%

“…Most of the centrosomal proteins studied here are expected to be expressed at low levels, and information about their abundance remains scarce. In comprehensive proteomics studies, key regulators of centriole duplication, including Plk4, Sas‐6, and STIL, were barely detectable, if they were detected at all (Beck et al , 2011; Nagaraj et al , 2011). For example, one extensive mass spectrometry‐based analysis of U2OS cells concluded that Sas‐6 is expressed at fewer than 500 copies per cell (Beck et al , 2011).…”

Section: Discussionmentioning

confidence: 99%

“…Comprehensive studies on the proteomes of cells, tissues, or organisms have been reported (e.g. Addona et al , 2009; Nilsson et al , 2010; Beck et al , 2011; Nagaraj et al , 2011; for review, see Bensimon et al , 2012; Kulak et al , 2014; Wilhelm et al , 2014; Hein et al , 2015; Richards et al , 2015), but accurate quantitative information on proteins expressed at low levels remains scarce. As a consequence, published estimates for the abundance of specific proteins sometimes vary over several orders of magnitude.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Quantitative analysis of human centrosome architecture by targeted proteomics and fluorescence imaging

et al. 2016

View full text Add to dashboard Cite

Centrioles are essential for the formation of centrosomes and cilia. While numerical and/or structural centrosomes aberrations are implicated in cancer, mutations in centriolar and centrosomal proteins are genetically linked to ciliopathies, microcephaly, and dwarfism. The evolutionarily conserved mechanisms underlying centrosome biogenesis are centered on a set of key proteins, including Plk4, Sas‐6, and STIL, whose exact levels are critical to ensure accurate reproduction of centrioles during cell cycle progression. However, neither the intracellular levels of centrosomal proteins nor their stoichiometry within centrosomes is presently known. Here, we have used two complementary approaches, targeted proteomics and EGFP‐tagging of centrosomal proteins at endogenous loci, to measure protein abundance in cultured human cells and purified centrosomes. Our results provide a first assessment of the absolute and relative amounts of major components of the human centrosome. Specifically, they predict that human centriolar cartwheels comprise up to 16 stacked hubs and 1 molecule of STIL for every dimer of Sas‐6. This type of quantitative information will help guide future studies of the molecular basis of centrosome assembly and function.

show abstract

Section: Discussionsupporting

confidence: 90%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Quantitative analysis of human centrosome architecture by targeted proteomics and fluorescence imaging

et al. 2016

View full text Add to dashboard Cite

show abstract

“…Recent developments in methods and instruments for mass spectrometry enable quantitative proteomics analysis of complex samples with good coverage (1)(2)(3)(4). Several techniques for quantification by mass spectrometry exist, both using isotopic labeling and label free methods (5,6).…”

mentioning

confidence: 99%

Defining, Comparing, and Improving iTRAQ Quantification in Mass Spectrometry Proteomics Data

Hultin‐Rosenberg

Forshed

Branca

et al. 2013

Molecular & Cellular Proteomics

View full text Add to dashboard Cite

The purpose of this study was to generate a basis for the decision of what protein quantities are reliable and find a way for accurate and precise protein quantification. To investigate this we have used thousands of peptide measurements to estimate variance and bias for quantification by iTRAQ (isobaric tags for relative and absolute quantification) mass spectrometry in complex human samples. A549 cell lysate was mixed in the proportions 2:2:1:1:2:2:1:1, fractionated by high resolution isoelectric focusing and liquid chromatography and analyzed by three mass spectrometry platforms; LTQ Orbitrap Velos, 4800 MALDI-TOF/TOF and 6530 Q-TOF. We have investigated how variance and bias in the iTRAQ reporter ions data are affected by common experimental variables such as sample amount, sample fractionation, fragmentation energy, and instrument platform. Based on this, we have suggested a concept for experimental design and a methodology for protein quantification. By using duplicate samples in each run, each experiment is validated based on its internal experimental variation. The duplicates are used for calculating peptide weights, unique to the experiment, which is used in the protein quantification. By weighting the peptides depending on reporter ion intensity, we can decrease the relative error in quantification at the protein level and assign a total weight to each protein that reflects the protein quantitation confidence. We also demonstrate the usability of this methodology in a cancer cell line experiment as well as in a clinical data set of lung cancer tissue samples. In conclusion, we have in this study developed a methodology for improved protein quantification in shotgun proteomics and introduced a way to assess quantification for proteins with few peptides. The experimental design and developed algorithms decreased the relative protein quantification error in the analysis of complex biological samples. Recent developments in methods and instruments for mass spectrometry enable quantitative proteomics analysis of complex samples with good coverage (1-4). Several techniques for quantification by mass spectrometry exist, both using isotopic labeling and label free methods (5, 6). Quantification by isotopic labeling can be done on precursor ion level or by quantifying isobaric label fragments in fragment spectra. Isotope-coded affinity tag (7), isobaric tags for relative and absolute quantification (iTRAQ) 1 (8), and stable isotope labeling by amino acids in cell culture (SILAC) (9) are among the most commonly used labeling methods based on stable isotopes. iTRAQ allows for simultaneous relative quantification of up to eight samples within a single run. Quantification by mass spectrometry is however a challenge, and several factors contribute to the uncertainty in the quantitative estimate; differences in labeling efficiency, protein digestion, precursor mixing, ion suppression, peak detection, data preprocessing, and data analysis (10). The quality of quantitation methods can be measured in terms of precision ...

show abstract

“…Using mass spectrometry, peptide fragments from a digested protein can be detected as mass spectral signals, which are matched to the theoretical peptide mass spectrum based on the protein sequence database to identify the protein. Currently, advanced mass spectrometry can identify approximately 12000 proteins in single human cells; the detection sensitivity can even be improved by using SRM/MRM technology [4,5]. However, mass spectrometry has its inherent limitations in protein identification, including the requirement for the large amount of samples, low identification rates for low-abundance proteins and low reproducibility from different laboratories [6,7].…”

mentioning

confidence: 99%

How to discover new proteins—translatome profiling

Zhang

Wang

2014

Sci. China Life Sci.

View full text Add to dashboard Cite

Deep proteome and transcriptome mapping of a human cancer cell line

Abstract: More than 10 000 proteins were identified by high-resolution mass spectrometry in a human cancer cell line. The data cover most of the functional proteome as judged by RNA-seq data and it reveals the expression range of different protein classes.

Cited by 936 publications

References 35 publications

Quantitative analysis of human centrosome architecture by targeted proteomics and fluorescence imaging

Quantitative analysis of human centrosome architecture by targeted proteomics and fluorescence imaging

Defining, Comparing, and Improving iTRAQ Quantification in Mass Spectrometry Proteomics Data

How to discover new proteins—translatome profiling

Contact Info

Product

Resources

About