Proteome Resolution by Two-Dimensional Gel Electrophoresis Varies with the Commercial Source of IPG Strips
Bibliographic record
Abstract
By facilitating reproducible first dimension separations, commercial immobilized pH gradient (IPG) strips enable high throughput and high-resolution proteomic analyses using two-dimensional gel electrophoresis (2DE). Amersham, Biorad, Invitrogen, and Sigma all market linear pH 3-10 IPG strips. We have applied optimized 2DE protocols with both membrane and soluble brain protein extracts to critically evaluate all four products. Resolved protein spots were quantitatively evaluated after carrying out these protocols using IPG strips from the four companies. Biorad and Amersham IPG strips resolved a high number of membrane and soluble proteins, respectively. Furthermore, Amersham IPG strips eluted the largest amount of protein into the second dimension gels and had the most protein remaining in the strip after 2DE. Biorad and Amersham IPG strips maintained a consistent linear pH 3-10 gradient, whereas those from Invitrogen appeared nonlinear or "compressed" within the central pH region. The gradient range within Sigma IPG strips appeared to be slightly less than pH 3-10, due to one extended pH unit within the gradient. Overall, all four commercially available IPG strips have the ability to resolve both membrane and soluble brain proteomes. The difference is that Amersham and Biorad do so more consistently and with better spot resolution. It appears that the physical/chemical nature of commercially available IPG strips can vary considerably, leading to marked differences in subsequent protein resolution in 2DE. These differences likely reflect variations in the uptake of proteins into the strips, and differences in the focusing and elution of proteins from the first to the second dimension. These differences would appear, in part, to underlie some inter-lab variations in the effective resolution of proteomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".