i-Tracker: For quantitative proteomics using iTRAQ™

Shadforth, Ian; Dunkley, Tom; Lilley, Kathryn S.; Bessant, Conrad

doi:10.1186/1471-2164-6-145

Cited by 274 publications

(193 citation statements)

References 9 publications

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“…Normalized iTRAQ reporter ion ratios were calculated from the uncentroided peak lists by using the recently developed I-TRACKER (38). Normalized reporter ion areas were calculated as follows: Normalized area A ϭ area A͞(area A ϩ area B ϩ area C ϩ area D).…”

Section: Methodsmentioning

confidence: 99%

Mapping the Arabidopsis organelle proteome

Dunkley

Hester

Shadforth

et al. 2006

Proc. Natl. Acad. Sci. U.S.A.

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A challenging task in the study of the secretory pathway is the identification and localization of new proteins to increase our understanding of the functions of different organelles. Previous proteomic studies of the endomembrane system have been hindered by contaminating proteins, making it impossible to assign proteins to organelles. Here we have used the localization of organelle proteins by the isotope tagging technique in conjunction with isotope tags for relative and absolute quantitation and 2D liquid chromatography for the simultaneous assignment of proteins to multiple subcellular compartments. With this approach, the density gradient distributions of 689 proteins from Arabidopsis thaliana were determined, enabling confident and simultaneous localization of 527 proteins to the endoplasmic reticulum, Golgi apparatus, vacuolar membrane, plasma membrane, or mitochondria and plastids. This parallel analysis of endomembrane components has enabled protein steady-state distributions to be determined. Consequently, genuine organelle residents have been distinguished from contaminating proteins and proteins in transit through the secretory pathway.endomembrane ͉ localization of organelle proteins by isotope tagging ͉ isotope tags for relative and absolute quantitation ͉ organelle proteomics P roteins are spatially organized according to their functions within the eukaryotic cell. Therefore, protein localization is an important step toward assigning functions to the thousands of uncharacterized proteins predicted by the genome-sequencing projects. Proteomics provides powerful tools for characterizing the protein contents of organelles. Confident protein localization, however, requires that either organelle preparations are free of contaminants or that techniques are used to discriminate between genuine organelle residents and contaminating proteins (1). Although reasonably pure preparations of some organelles, such as mitochondria, can be achieved, the components of the endomembrane system so far have proved recalcitrant to purification (2, 3). The constituent organelles of the endomembrane system have similar sizes and densities, making them difficult to separate. In addition, the proteins that reside within this system are in a constant state of flux. Endomembrane proteins traffic through the system en route to their final destination; for example, plasma membrane (PM) proteins travel although the endoplasmic reticulum (ER) and the Golgi apparatus before reaching the cell surface. Proteins within the endomembrane system also cycle between compartments; for example, ER residents continuously escape to the Golgi apparatus and are retrieved in COPI vesicles (4). Consequently, it is not sufficient merely to identify the proteins within a single organelle-enriched fraction. Instead, the steady-state distributions of proteins within the whole endomembrane system must be determined if a realistic insight into the subcellular localization of endomembrane proteins is to be achieved.Localization of organelle proteins by...

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Section: Methodsmentioning

confidence: 99%

Mapping the Arabidopsis organelle proteome

Dunkley

Hester

Shadforth

et al. 2006

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

508

428

View full text Add to dashboard Cite

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“…There are a large variety of excellent tools available, which are targeted in the main towards particular approaches, instruments, vendors, third-party software and/or formats [24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43]. Table 1 summarises existing freely available quantitative proteomic software.…”

Section: Existing Softwarementioning

confidence: 99%

“…In the table, there are five tools relating to SEQUEST-based analyses for single isotope and ICAT studies [32][33][34][35]40], three relating specifically to iTRAQ ™ [24,38,43] and two relating to solely 16 O/ 18 O labelling methods [37,41,42]. They were chosen because sufficient details of the algorithm have been made available in the respective publications.…”

Section: Extracting and Calculating Quantitative Datamentioning

confidence: 99%

“…The peptide ratio is determined by the ratio between light and heavy chromatographic peak areas (i) Each peptide ratio is normalised by the median of all peptide ratios from one or multiple raw files (ii) The protein ratio is estimated from the median of the corresponding peptide ratios, or by using the one-step biweight algorithm (iii) The significance of a protein ratio for a mixture of two samples is estimated using a t test (iv) The significance of a protein ratio for two groups of samples is estimated by first by applying the Student's t test on each protein and then using the Westfall and Young step-down method to adjust the probability value of the protein ratio I-Tracker [24] Each MS/MS spectra 114-117 m/z in MS/MS spectrum (i) Peak selection, (ii) isotope impurity correction, (iii) normalisation of peak area Protein ratios not calculated A similar choice is presented when handling the ion chromatogram. Figure 3 shows two smoothed ion chromatograms, for the heavy and light species, where a chromatographic peak is defined as a subset of the total ion chromatogram.…”

Section: Extracting and Calculating Quantitative Datamentioning

confidence: 99%

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Capture and analysis of quantitative proteomic data

et al. 2007

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Whilst the array of techniques available for quantitative proteomics continues to grow, the attendant bioinformatic software tools are similarly expanding in number. The data capture and analysis of such quantitative data is obviously crucial to the experiment and the methods used to process it will critically affect the quality of the data obtained. These tools must deal with a variety of issues, including identification of labelled and unlabelled peptide species, location of the corresponding MS scans in the experiment, construction of representative ion chromatograms, location of the true peptide ion chromatogram start and end, elimination of background signal in the mass spectrum and chromatogram and calculation of both peptide and protein ratios/abundances. A variety of tools and approaches are available, in part restricted by the nature of the experiment to be performed and available instrumentation. Currently, although there is no single consensus on precisely how to calculate protein and peptide abundances, many common themes have emerged which identify and reduce many of the key sources of error. These issues will be discussed, along with those relating to deposition of quantitative data. At present, mature data standards for quantitative proteomics are not yet available, although formats are beginning to emerge.

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“…Isotope-labelling methods, as seen on Figure 2, are gel-free procedures that introduce stable isotope tags to proteins through chemical reactions using isotope-coded affinity tags (ICAT) (28) and isobaric tag for relative and absolute quantitation (iTRAQ) (29), or through metabolic labelling with isotope labelled amino acids in cell culture (SILAC) (30).…”

Section: Isotope-labelled Mass Spectrometrymentioning

confidence: 99%