Quantitative and reproducible two-dimensional gel analysis using Phoretix 2D Full

Mahon, Piers; Dupree, Paul

doi:10.1002/1522-2683(200106)22:10<2075::aid-elps2075>3.0.co;2-c

Cited by 88 publications

(56 citation statements)

References 21 publications

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“…The first three PCs accounted for the main differences existing between the four groups: PC 1 explains the information related to the two cell lines; PC 2 carries the information about the TSA effect, mainly for the Paca44 cell line; PC 3 carries the information about cellular sensitivity to TSA, mainly for the T3M4 cell line. Cluster analysis was then performed on the three relevant PCs by means of the Ward method (Euclidean distances were used in the calculations).…”

Section: Pca and Cluster Analysismentioning

confidence: 99%

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Numerical approaches for quantitative analysis of two‐dimensional maps: A review of commercial software and home‐made systems

et al. 2005

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The present review attempts to cover a number of methods that have appeared in the last few years for performing quantitative proteome analysis. However, due to the large number of methods described for both electrophoretic and chromatographic approaches, we have limited this review to conventional two-dimensional (2-D) map analysis which couples orthogonally a charge-based step (isoelectric focusing) to a size-based separation step (sodium dodecyl sulfateelectrophoresis). The first and oldest method applied to 2-D map data reduction is based on statistical analysis performed on sets of gels via powerful software packages, such as Melanie, PDQuest, Z3 and Z4000, Phoretix and Progenesis. This method calls for separately running a number of replicas for control and treated samples. The two sets of data are then merged and compared via a number of software packages which we describe. In addition to commerciallyavailable systems, a number of home made approaches for 2-D map comparison have been recently described and are also reviewed. They are based on fuzzyfication of the digitized 2-D gel image coupled to linear discriminant analysis, three-way principal component analysis or a combination of principal component analysis and soft-independent modeling of class analogy. These statistical tools appear to perform well in differential proteomic studies.

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Section: Pca and Cluster Analysismentioning

confidence: 99%

“…Other reports assess just a single product, e.g. Phoretix 2-D full [3]; Compugen's Z4000 [4]. Other articles deal with general aspects of such algorithms, such as point pattern matching, reproducibility, matching efficiency etc.…”

Section: Introductionmentioning

confidence: 99%

Numerical approaches for quantitative analysis of two‐dimensional maps: A review of commercial software and home‐made systems

et al. 2005

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“…manual intervention to verify the steps of detection of protein spots and of pairing of protein spots between treatments). Table 2 reveals there to be a significant difference in the total number of protein spots (specific 1 common protein spots) observed between the two types of analyses As suggested by other authors, manual intervention is still necessary for the differential analysis using these softwares [8,45,[59][60][61][62].…”

Section: Misuses Of Softwaresmentioning

confidence: 99%

The pitfalls of proteomics experiments without the correct use of bioinformatics tools

Biron¹,

Brun²,

Lefèvre³

et al. 2006

Proteomics

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The elucidation of the entire genomic sequence of various organisms, from viruses to complex metazoans, most recently man, is undoubtedly the greatest triumph of molecular biology since the discovery of the DNA double helix. Over the past two decades, the focus of molecular biology has gradually moved from genomes to proteomes, the intention being to discover the functions of the genes themselves. The postgenomic era stimulated the development of new techniques (e.g. 2-DE and MS) and bioinformatics tools to identify the functions, reactions, interactions and location of the gene products in tissues and/or cells of living organisms. Both 2-DE and MS have been very successfully employed to identify proteins involved in biological phenomena (e.g. immunity, cancer, host-parasite interactions, etc.), although recently, several papers have emphasised the pitfalls of 2-DE experiments, especially in relation to experimental design, poor statistical treatment and the high rate of 'false positive' results with regard to protein identification. In the light of these perceived problems, we review the advantages and misuses of bioinformatics tools -from realisation of 2-DE gels to the identification of candidate protein spots -and suggest some useful avenues to improve the quality of 2-DE experiments. In addition, we present key steps which, in our view, need to be to taken into consideration during such analyses. Lastly, we present novel biological entities named 'interactomes', and the bioinformatics tools developed to analyse the large proteinprotein interaction networks they form, along with several new perspectives of the field.

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“…The twelve 2D gels of A431 and the 12 gels of the A549 concentrated conditioned media were analysed using Phoretixt 2D software version 2003.02, Non-Linear Dynamics (Newcastle upon Tyne, UK) (Mahon and Dupree, 2001). Average gels were created from the four gels for each type of treatment: 'Not treated', 'DMSO (drug vehicle) treated' and 'Gefitinib' treated, and the maximum number of gels where the spots may be absent were one in four.…”

Section: Image Analysismentioning

confidence: 99%

Proteomic identification of secreted proteins as surrogate markers for signal transduction inhibitor activity

McClelland

Gullick

2007

Br J Cancer

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Epidermal growth factor receptor is a potential target for cancer treatment and new small-molecule tyrosine kinase inhibitor drugs have been designed to inhibit its activity. In this work we identify potential surrogate markers of drug activity using a proteomic analysis. Two-dimensional electrophoresis was optimised to compare expression patterns of proteins secreted from the cancer cell lines A431 and A549 treated with Gefitinib (Iressa) vs untreated or vehicle-only-treated samples. Upregulated or downregulated proteins were detected using Phoretix 2D image analysis software. Several proteins were then identified using matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometry. In one case, upregulation of Protein Disulphide Isomerase in response to Gefitinib was confirmed by Western blot analysis, and the response was shown to be concentration dependent. The identification of surrogate markers may be of use for the evaluation of new drugs, in preclinical models, in clinical trials and in the therapy of individual patients to give optimal biological drug doses.

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Quantitative and reproducible two-dimensional gel analysis using Phoretix 2D Full

Cited by 88 publications

References 21 publications

Numerical approaches for quantitative analysis of two‐dimensional maps: A review of commercial software and home‐made systems

Numerical approaches for quantitative analysis of two‐dimensional maps: A review of commercial software and home‐made systems

The pitfalls of proteomics experiments without the correct use of bioinformatics tools

Proteomic identification of secreted proteins as surrogate markers for signal transduction inhibitor activity

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