Analysis of 2D-gel images for detection of protein spots using a novel non-separable wavelet based method

Sengar, Ratnesh Singh; Upadhyay, Ashutosh; Singh, Manjit; Gadre, Vikram M.

doi:10.1016/j.bspc.2015.10.013

Cited by 9 publications

(9 citation statements)

References 36 publications

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“…Interestingly, it has been shown that the performance of Delta2D improves with increased noise . nIRFD images processed in Delta2D presented granular residual backgrounds to a greater extent than 37 μm densitometry images following automated background subtraction, corroborating that nIRFD‐imaged gel backgrounds were measurably less uniform (i.e.…”

Section: Resultsmentioning

confidence: 78%

“…It is possible that the measured decrease in 1DE S/N with 200 μm nIRFD may in part be attributed to the stain utilised, consistent with some signal from stained matrix despite the expectation that primarily only protein‐bound CBB should fluoresce . Again, however, evidence suggests that poor S/N would not have so negatively impacted Delta2D analysis , indicating that low image resolution was the primary cause of the decreased 2DE DS observed. Certainly, the Delta2D imaging guide (https://www.decodon.com) highlights the need for adequate image resolution for optimal analysis outcomes.…”

Section: Resultsmentioning

confidence: 79%

“…However, such instrumentation, which generally utilise lamps and LEDs rather than lasers, may be expected to be less sensitive (depending on the fluorophore used) due to broader wavelength excitation and emission hardware. Due focus should continue to be placed on improving imaging and analysis approaches in order to maximise outcomes of proteomic investigations, as recently demonstrated by a number of groups . It is clear that the capacity for proteome coverage and detection using 2DE and cCBB staining (and thus likely many other stains) has in general been grossly underestimated .…”

Section: Resultsmentioning

confidence: 99%

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Coomassie staining provides routine (sub)femtomole in‐gel detection of intact proteoforms: Expanding opportunities for genuine Top‐down Proteomics

et al. 2017

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Modified colloidal Coomassie Brilliant Blue (cCBB) staining utilising a novel destain protocol and near-infrared fluorescence detection (nIRFD) rivals the in-gel protein detection sensitivity (DS) of SYPRO Ruby. However, established DS estimates are likely inaccurate in terms of 2DE-resolved proteoform 'spots' since DS is routinely measured from comparatively diffuse protein 'bands' following wide-well 1DE. Here, cCBB DS for 2DE-based proteomics was more accurately determined using narrow-well 1DE. As precise estimates of protein standard monomer concentrations are essential for accurate quantitation, coupling UV absorbance with gel-based purity assessments is described. Further, as cCBB is compatible with both nIRFD and densitometry, the impacts of imaging method (and image resolution) on DS were assessed. Narrow-well 1DE enabled more accurate quantitation of cCBB DS for 2DE, achieving (sub)femtomole DS with either nIRFD or densitometry. While densitometry offers comparative simplicity and affordability, nIRFD has the unique potential for enhanced DS with Deep Imaging. Higher-resolution nIRFD also improved analysis of a 2DE-resolved proteome, surpassing the DS of standard nIRFD and densitometry, with nIRFD Deep Imaging further maximising proteome coverage. cCBB DS for intact proteins rivals that of mass spectrometry (MS) for peptides in complex mixtures, reaffirming that 2DE-MS currently provides the most routine, broadly applicable, robust, and information-rich Top-down approach to Discovery Proteomics.

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Section: Resultsmentioning

confidence: 78%

Section: Resultsmentioning

confidence: 79%

Section: Resultsmentioning

confidence: 99%

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Coomassie staining provides routine (sub)femtomole in‐gel detection of intact proteoforms: Expanding opportunities for genuine Top‐down Proteomics

et al. 2017

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“…2-DGE images inevitably exhibit anomalies caused by sample preparation techniques and the imaging system used to acquire the digital images [22] . The most common anomalies in 2-DGE images are oversaturated, faint, or fuzzy spots, vertical and horizontal streaking, overlapping spots, and noise [13] , [23] . Figure 1 shows a 2-DGE image with the most common anomalies.…”

Section: Preprocessing Of 2-dge Imagesmentioning

confidence: 99%

“…Many computational applications are available for processing and analyzing 2-DGE images, such as MELANIE, PDQuest, Z3, Progenesis Workstation, ProteomeWeaver, ProteinMine, Delta2D, and DeCyder [12] , [13] . Given that one cell can express around ten thousand proteins, 2-DGE needs an effective computational tool that can process large volumes of information [14] .…”

Section: Introductionmentioning

confidence: 99%

Preprocessing of 2-Dimensional Gel Electrophoresis Images Applied to Proteomic Analysis: A Review

Goez

Torres-Madronero

Röthlisberger

et al. 2018

Genomics, Proteomics &Amp; Bioinformatics

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Various methods and specialized software programs are available for processing two-dimensional gel electrophoresis (2-DGE) images. However, due to the anomalies present in these images, a reliable, automated, and highly reproducible system for 2-DGE image analysis has still not been achieved. The most common anomalies found in 2-DGE images include vertical and horizontal streaking, fuzzy spots, and background noise, which greatly complicate computational analysis. In this paper, we review the preprocessing techniques applied to 2-DGE images for noise reduction, intensity normalization, and background correction. We also present a quantitative comparison of non-linear filtering techniques applied to synthetic gel images, through analyzing the performance of the filters under specific conditions. Synthetic proteins were modeled into a two-dimensional Gaussian distribution with adjustable parameters for changing the size, intensity, and degradation. Three types of noise were added to the images: Gaussian, Rayleigh, and exponential, with signal-to-noise ratios (SNRs) ranging 8–20 decibels (dB). We compared the performance of wavelet, contourlet, total variation (TV), and wavelet-total variation (WTTV) techniques using parameters SNR and spot efficiency. In terms of spot efficiency, contourlet and TV were more sensitive to noise than wavelet and WTTV. Wavelet worked the best for images with SNR ranging 10–20 dB, whereas WTTV performed better with high noise levels. Wavelet also presented the best performance with any level of Gaussian noise and low levels (20–14 dB) of Rayleigh and exponential noise in terms of SNR. Finally, the performance of the non-linear filtering techniques was evaluated using a real 2-DGE image with previously identified proteins marked. Wavelet achieved the best detection rate for the real image.

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Computational Methods for Proteome Analysis

Navakauskienė

Navakauskas

Borutinskaitė

et al. 2021

Epigenetics and Proteomics of Leukemia

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Analysis of 2D-gel images for detection of protein spots using a novel non-separable wavelet based method

Cited by 9 publications

References 36 publications

Coomassie staining provides routine (sub)femtomole in‐gel detection of intact proteoforms: Expanding opportunities for genuine Top‐down Proteomics

Coomassie staining provides routine (sub)femtomole in‐gel detection of intact proteoforms: Expanding opportunities for genuine Top‐down Proteomics

Preprocessing of 2-Dimensional Gel Electrophoresis Images Applied to Proteomic Analysis: A Review

Computational Methods for Proteome Analysis

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