2de gels  (Bio-Rad)

Journal: Scientific reports

Article Title: Comparative in vitro immunoreactivity and protein analysis of Trimeresurus albolabris and Tropidolaemus wagleri venoms.

doi: 10.1038/s41598-025-97032-0

Figure Lengend Snippet: Fig. 2. Two-dimensional (2DE) separations and immunoblot analysis of Trimeresurus albolabris venom. 2DE gels stained with silver stain, spots were numbered, grouped and alphabetically listed from A–P (A). 2DE immunoblot of Trimeresurus albolabris proteins probed with hemato polyvalent antivenom (B). Identification and relative classification of immunoreactive proteins (C) and non-immunoreactive proteins (D) in Trimeresurus albolabris venom .

Article Snippet: The separated polypeptide spots from 2DE gels were transferred to nitrocellulose membrane for 90 min at 18 V on a Trans-blot semi-dry Transfer CellTM (Biorad) in semi-dry transfer buffer (48 mM Tris and 2.93 g glycine) pH 9.2 containing 20% methanol.

Techniques: Western Blot, Staining, Silver Staining

Journal: Scientific reports

Article Title: Comparative in vitro immunoreactivity and protein analysis of Trimeresurus albolabris and Tropidolaemus wagleri venoms.

doi: 10.1038/s41598-025-97032-0

Figure Lengend Snippet: Fig. 3. 2DE separations and immunoblot analysis of Tropidolaemus wagleri venom. 2DE gels stained with silver stain, spots were numbered, grouped and alphabetically listed from A–K (A). 2DE immunoblot of Tropidolaemus wagleri probed with hemato polyvalent antivenom (B). Identification and relative classification of immunoreactive proteins (C) and non-immunoreactive proteins (D) in Tropidolaemus wagleri venom.

Article Snippet: The separated polypeptide spots from 2DE gels were transferred to nitrocellulose membrane for 90 min at 18 V on a Trans-blot semi-dry Transfer CellTM (Biorad) in semi-dry transfer buffer (48 mM Tris and 2.93 g glycine) pH 9.2 containing 20% methanol.

Techniques: Western Blot, Staining, Silver Staining

Journal: Biomedicines

Article Title: Comparative Proteomic Assessment of Normal vs. Polyhydramnios Amniotic Fluid Based on Computational Analysis

doi: 10.3390/biomedicines10081821

Figure Lengend Snippet: Comparative analysis of 2DE proteome maps characteristic for normal and polyhydramnios pregnancies. The proteins were resolved by 2DE, pH range 3–11, and Excel Gel SDS, gradient 8–18%. 2DE images of proteins of amniotic fluid of normal pregnancy (AFN, G1; blue in G1 + G2 and amniotic fluid of polyhydramnios pregnancy (AFP, G2; orange in G1 + G2) were superposed and presented in G1 + G2. Arrows and numbers in the 2DE maps indicate the positions of proteins supplied to MALDI-TOF MS/MS and identified. Spot labels are the same as in . Molecular weight (Mw) markers are presented on the left. Representative images from one of three experiments showing similar results are shown.

Article Snippet: The prototype is executed in MatlabTM environment (The MathWorks, Inc., Natick, MA, USA) and has integral original 2DE gel image processing algorithms as tools for specific tasks: Image preparation tools: image cropping (to remove excess areas), spot labelling, master gel selection (to align the group of gels), molecular mass markers’ calibration (to delineate area of MM marker and input of MM values), pI calibration (to input positions of known pI values); Image preprocessing related tools: image smoothing (to eliminate impulse noise), background elimination (to remove variations of background staining), individual image warping (to straighten protein migration paths); Image segmentation tools: 2DE image splitting (to split image into primary segments), segmented area evaluation (to highlight uncertain segmentations of protein spots for the user), editing of segments (to manually edit protein spots in order to remove false negatives and positives of segmentation by merging, splitting, adding, or removing areas); Image alignment tools: initial registration (to automatically detect some high confident control points for initial image registration), spot pairing and concluding image alignment (to find correspondences between spots), manual editing of alignment vectors (to remove mismatches and add new matches between images); Quantitative analysis tools: spot quantification (to measure normalized quantities of spots), changes evaluation (to calculate change ratios); Visualization tools: 3D viewer (to display small area of image as surface), image fusion (to display overlay of two images using pseudocolors).

Techniques: Tandem Mass Spectroscopy, Molecular Weight

Journal: Biomedicines

Article Title: Comparative Proteomic Assessment of Normal vs. Polyhydramnios Amniotic Fluid Based on Computational Analysis

doi: 10.3390/biomedicines10081821

Figure Lengend Snippet: The summarized search results (by UniProt, Expasy) of proteins identified from 2DE gels representing protein maps of amniotic fluid of normal and polyhydramnios pregnancies fractionated in the pI 3–11 range. An increase in spot intensity yields a positive fold-change and a decrease accordingly a negative fold-change in AFN/AFP (marked as G1/G2). a ) AC—accession number; b ) Score—protein Score C.I. %; c ) Match—Matching (sequence coverage, %); d ) TP—Theoretical Peptides; e ) DP—Digest Peptides; f ) FC—Fold Change.

Article Snippet: The prototype is executed in MatlabTM environment (The MathWorks, Inc., Natick, MA, USA) and has integral original 2DE gel image processing algorithms as tools for specific tasks: Image preparation tools: image cropping (to remove excess areas), spot labelling, master gel selection (to align the group of gels), molecular mass markers’ calibration (to delineate area of MM marker and input of MM values), pI calibration (to input positions of known pI values); Image preprocessing related tools: image smoothing (to eliminate impulse noise), background elimination (to remove variations of background staining), individual image warping (to straighten protein migration paths); Image segmentation tools: 2DE image splitting (to split image into primary segments), segmented area evaluation (to highlight uncertain segmentations of protein spots for the user), editing of segments (to manually edit protein spots in order to remove false negatives and positives of segmentation by merging, splitting, adding, or removing areas); Image alignment tools: initial registration (to automatically detect some high confident control points for initial image registration), spot pairing and concluding image alignment (to find correspondences between spots), manual editing of alignment vectors (to remove mismatches and add new matches between images); Quantitative analysis tools: spot quantification (to measure normalized quantities of spots), changes evaluation (to calculate change ratios); Visualization tools: 3D viewer (to display small area of image as surface), image fusion (to display overlay of two images using pseudocolors).

Techniques: Sequencing, Clinical Proteomics, Membrane

Journal: Biomedicines

Article Title: Comparative Proteomic Assessment of Normal vs. Polyhydramnios Amniotic Fluid Based on Computational Analysis

doi: 10.3390/biomedicines10081821

Figure Lengend Snippet: The summarized search results (by UniProt, Expasy) of proteins identified from 2DE gels representing protein maps of amniotic fluid of polyhydramnios pregnancy fractionated in pI 3–11 and pI 4–7 range. a ) AC—accession number; b ) Score—protein Score C.I. %; c ) Match—Matching (sequence coverage, %); d ) TP—Theoretical Peptides; e ) DP—Digest Peptides; f ) FC—Fold Change.

Article Snippet: The prototype is executed in MatlabTM environment (The MathWorks, Inc., Natick, MA, USA) and has integral original 2DE gel image processing algorithms as tools for specific tasks: Image preparation tools: image cropping (to remove excess areas), spot labelling, master gel selection (to align the group of gels), molecular mass markers’ calibration (to delineate area of MM marker and input of MM values), pI calibration (to input positions of known pI values); Image preprocessing related tools: image smoothing (to eliminate impulse noise), background elimination (to remove variations of background staining), individual image warping (to straighten protein migration paths); Image segmentation tools: 2DE image splitting (to split image into primary segments), segmented area evaluation (to highlight uncertain segmentations of protein spots for the user), editing of segments (to manually edit protein spots in order to remove false negatives and positives of segmentation by merging, splitting, adding, or removing areas); Image alignment tools: initial registration (to automatically detect some high confident control points for initial image registration), spot pairing and concluding image alignment (to find correspondences between spots), manual editing of alignment vectors (to remove mismatches and add new matches between images); Quantitative analysis tools: spot quantification (to measure normalized quantities of spots), changes evaluation (to calculate change ratios); Visualization tools: 3D viewer (to display small area of image as surface), image fusion (to display overlay of two images using pseudocolors).

Techniques: Sequencing, Membrane

Journal: Biomedicines

Article Title: Comparative Proteomic Assessment of Normal vs. Polyhydramnios Amniotic Fluid Based on Computational Analysis

doi: 10.3390/biomedicines10081821

Figure Lengend Snippet: Comparative analysis of 2DE protein maps corresponding amniotic fluid of polyhydramnios pregnancy fractionated in different pI range. ( A ) proteins corresponding amniotic fluid of polyhydramnios pregnancy (AFP), fractionated in different pI range: pI 3–11 (G2, blue in G2 + G3) and pI 4–7 (G3, orange in G2 + G3) range and Excel Gel SDS, gradient 8–18%. Arrows and numbers in the 2DE maps indicate the positions of proteins supplied to MALDI-TOF MS/MS and identified. Spot labels for the proteins fractionated in the range pI 3–11 are the same as in . Spot labels for the proteins fractionated in the range pI 4–7 are the same as in . ( B ) Computational analysis of several protein groups is performed to evaluate their distribution in different pI value ranges. It shows that the same protein level with different pI changes because of modification level. In , the proteins’ spot distribution corresponding to the different modification level is presented (column— Share, %). Representative images from one of three experiments showing similar results are shown.

Article Snippet: The prototype is executed in MatlabTM environment (The MathWorks, Inc., Natick, MA, USA) and has integral original 2DE gel image processing algorithms as tools for specific tasks: Image preparation tools: image cropping (to remove excess areas), spot labelling, master gel selection (to align the group of gels), molecular mass markers’ calibration (to delineate area of MM marker and input of MM values), pI calibration (to input positions of known pI values); Image preprocessing related tools: image smoothing (to eliminate impulse noise), background elimination (to remove variations of background staining), individual image warping (to straighten protein migration paths); Image segmentation tools: 2DE image splitting (to split image into primary segments), segmented area evaluation (to highlight uncertain segmentations of protein spots for the user), editing of segments (to manually edit protein spots in order to remove false negatives and positives of segmentation by merging, splitting, adding, or removing areas); Image alignment tools: initial registration (to automatically detect some high confident control points for initial image registration), spot pairing and concluding image alignment (to find correspondences between spots), manual editing of alignment vectors (to remove mismatches and add new matches between images); Quantitative analysis tools: spot quantification (to measure normalized quantities of spots), changes evaluation (to calculate change ratios); Visualization tools: 3D viewer (to display small area of image as surface), image fusion (to display overlay of two images using pseudocolors).

Techniques: Tandem Mass Spectroscopy, Modification

Journal: Biomedicines

Article Title: Comparative Proteomic Assessment of Normal vs. Polyhydramnios Amniotic Fluid Based on Computational Analysis

doi: 10.3390/biomedicines10081821

Figure Lengend Snippet: Identified AFP proteins—those expressions are higher in comparison to proteome associated with normal pregnancy in 2DE gels with pI 3–11 ranges (right panel) and AFP proteins, the spots number of which (proportionate to modification) in AFP pI 4–7 differ in comparison to fractionated in pI 3–11 range (left panel).

Article Snippet: The prototype is executed in MatlabTM environment (The MathWorks, Inc., Natick, MA, USA) and has integral original 2DE gel image processing algorithms as tools for specific tasks: Image preparation tools: image cropping (to remove excess areas), spot labelling, master gel selection (to align the group of gels), molecular mass markers’ calibration (to delineate area of MM marker and input of MM values), pI calibration (to input positions of known pI values); Image preprocessing related tools: image smoothing (to eliminate impulse noise), background elimination (to remove variations of background staining), individual image warping (to straighten protein migration paths); Image segmentation tools: 2DE image splitting (to split image into primary segments), segmented area evaluation (to highlight uncertain segmentations of protein spots for the user), editing of segments (to manually edit protein spots in order to remove false negatives and positives of segmentation by merging, splitting, adding, or removing areas); Image alignment tools: initial registration (to automatically detect some high confident control points for initial image registration), spot pairing and concluding image alignment (to find correspondences between spots), manual editing of alignment vectors (to remove mismatches and add new matches between images); Quantitative analysis tools: spot quantification (to measure normalized quantities of spots), changes evaluation (to calculate change ratios); Visualization tools: 3D viewer (to display small area of image as surface), image fusion (to display overlay of two images using pseudocolors).

Techniques: Comparison, Modification, Expressing, Clinical Proteomics, Membrane