Off-line LC-MALDI techniques for the identification of proteins, post-translational modifications and protein-protein interactions in proteomic studies
Bibliographic record
Abstract
Cells process an affay of intra-and extra-cellular signals needed to coordinate a variety of activities such as cell division, movement and differentiation.However, upon closer inspection of these networks, signal transduction can be broken down to a series of protein-protein interactions which are often modulated by the presence (or absence) of sequence specific modifications.While deciphering these events is extremely important, proteome-level analyses of these networks has proven to be a challenge due to the complex nature of biological samples.Although large-scale automation has revolutionized the field of proteomics, little ground has been gained in the development of robust microvolume approaches for one of the most commonly performed tasks within the life sciences, the purification of protein samples.To address these problems, we have set out to develop novel separation techniques for the characterization of protein-protein interactions and protein phosphorylation by mass spectrometry.To aid studies, a vacuumdriven LC device was developed for the separation and MALDI deposition of subpicomole amounts of material for MS and MS/MS analyses.To demonstrate utility of this device, we set out to identify novel protein-protein interactions of zonula occludens-1 (zo-1), a member of the MAGUK family of membrane-associated adaptor proteins.using a GST-fusion protein incorporating the PDZI domain of ZO-1, interactions involving the protein domain were pulled-down for proteomic identification.Over the course of the study, several cortical scaffolding proteins were identified, including alpha- actinin-4.Further in-depth analysis of the interaction between ZO-1 and alpha-actinin-4 demonstrated the interaction existed within a wide variety of cell and tissue types.lnterestingly, alpha-actinin-1, a protein having high sequence identity (86%) to alpha-actinin-4, demonstrated no affiliation with the ZO-1 protein.ln the final chapter, an analytical method to increase phosphopeptide detection was developed and demonstrated based upon the off-line LC-MALDI platform.Here, a strategy employing LC retention time prediction was used to enhance the detection of low abundance phosphopeptides in a hypothesis-driven manner.while many aspects of the research presented are proof-of-concept in nature, developments of these methods are expected to help researchers uncover dynamic events associated with cell signal transduction.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".