Preventing and troubleshooting artefacts in saturation labelled fluorescence 2‐D difference gel electrophoresis (saturation DiGE)

McNamara, Laura E.; Kantawong, Fahsai; Dalby, Matthew J.; Riehle, Mathis O.; Burchmore, Richard

doi:10.1002/pmic.201100135

Cited by 12 publications

(6 citation statements)

References 32 publications

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“…Differential gel electrophoresis, DiGE, was reported for the first time in 1997 , however only a small number of plant proteomics work have used this technology since 2006 (for a review see ). This methodology has two major disadvantages in plant systems: it is difficult to get a reproducible labeling and it is pricey .…”

Section: Methodological Evolution In Plant Proteomicsmentioning

confidence: 99%

Fourteen years of plant proteomics reflected in Proteomics: Moving from model species and 2DE‐based approaches to orphan species and gel‐free platforms

et al. 2015

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In this article, the topic of plant proteomics is reviewed based on related papers published in the journal Proteomics since publication of the first issue in 2001. In total, around 300 original papers and 41 reviews published in Proteomics between 2000 and 2014 have been surveyed. Our main objective for this review is to help bridge the gap between plant biologists and proteomics technologists, two often very separate groups. Over the past years a number of reviews on plant proteomics have been published . To avoid repetition we have focused on more recent literature published after 2010, and have chosen to rather make continuous reference to older publications. The use of the latest proteomics techniques and their integration with other approaches in the "systems biology" direction are discussed more in detail. Finally we comment on the recent history, state of the art, and future directions of plant proteomics, using publications in Proteomics to illustrate the progress in the field. The review is organized into two major blocks, the first devoted to provide an overview of experimental systems (plants, plant organs, biological processes) and the second one to the methodology.

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Section: Methodological Evolution In Plant Proteomicsmentioning

confidence: 99%

Fourteen years of plant proteomics reflected in Proteomics: Moving from model species and 2DE‐based approaches to orphan species and gel‐free platforms

et al. 2015

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“…However, DiGE does not change the need to ensure that an equal amount of each sample is mixed prior to IEF and may experience differences in labelling efficiency in different samples. Preferential labelling has been reported [54,55,56] and labelling could be altered if PTMs block the chemical group on a proteoform that the dye molecule reacts with or if pH is not in the correct range [57]. Protein reference standards are available for 2D-PAGE but their use is rare.…”

Section: Pre-digestion/digestion Normalizationmentioning

confidence: 99%

What is Normalization? The Strategies Employed in Top-Down and Bottom-Up Proteome Analysis Workflows

et al. 2019

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The accurate quantification of changes in the abundance of proteins is one of the main applications of proteomics. The maintenance of accuracy can be affected by bias and error that can occur at many points in the experimental process, and normalization strategies are crucial to attempt to overcome this bias and return the sample to its regular biological condition, or normal state. Much work has been published on performing normalization on data post-acquisition with many algorithms and statistical processes available. However, there are many other sources of bias that can occur during experimental design and sample handling that are currently unaddressed. This article aims to cast light on the potential sources of bias and where normalization could be applied to return the sample to its normal state. Throughout we suggest solutions where possible but, in some cases, solutions are not available. Thus, we see this article as a starting point for discussion of the definition of and the issues surrounding the concept of normalization as it applies to the proteomic analysis of biological samples. Specifically, we discuss a wide range of different normalization techniques that can occur at each stage of the sample preparation and analysis process.

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“…The pH of the sample buffer was suggested to be in the range of pH 6.5–7.5 , as the maleimide group is specific for SH groups at a pH below neutrality . Complete labeling of all cysteine residues must be ensured, therefore preliminary experiments to determine the correct amount of Tris‐(2‐carboxyethyl) phosphine and label to use must be conducted (for thorough guidelines, see ). For subsequent protein identification by MS, a preparative gel with a higher protein load should be prepared.…”

Section: Technical Aspects Of 2d Digementioning

confidence: 99%

State of the art of 2D DIGE

Arentz

Weiland

Oehler

et al. 2015

Proteomics Clinical Apps

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Difference gel electrophoresis enables the accurate quantification of changes in the proteome including combinations of PTMs and protein isoform expression. Here, we review recent advances in study design, image acquisition, and statistical analysis. We also compare DIGE to established and emerging mass spectrometric analysis technologies. Despite these recent advances in MS and the still unsolved limitations of 2DE to map hydrophobic, high molecular weight proteins with extreme pIs, DIGE remains the most comprehensive top-down method to study changes in abundance of intact proteins.

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Preventing and troubleshooting artefacts in saturation labelled fluorescence 2‐D difference gel electrophoresis (saturation DiGE)

Cited by 12 publications

References 32 publications

Fourteen years of plant proteomics reflected in Proteomics: Moving from model species and 2DE‐based approaches to orphan species and gel‐free platforms

Fourteen years of plant proteomics reflected in Proteomics: Moving from model species and 2DE‐based approaches to orphan species and gel‐free platforms

What is Normalization? The Strategies Employed in Top-Down and Bottom-Up Proteome Analysis Workflows

State of the art of 2D DIGE

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