Tracking Protein Expression, Post‐translational Modifications and Interactions with High Content Antibody Microarrays
Bibliographic record
Abstract
High content antibody microarrays are powerful tools to evaluate alterations in the levels and post‐translational status of hundreds of proteins of interest with only microgram amounts of crude cell and tissue lysate protein. However, interpretations of the results from traditional antibody microarray approaches have been hampered by the problems associated with sample preparation and protein detection, even when potent and specific antibodies are printed on these arrays. The Kinex™ KAM‐900P and KAM‐1150E antibody microarrays permitted semi‐quantitative measurements of the expressions, post‐translational modifications, and interactions of proteins with as little as 25 μg of lysate proteins. When used in combination, these microarrays utilize approximately 1250 different pan‐specific and 600 phosphosite‐specific antibodies for tracking protein kinases, phosphatases and other low abundance regulatory proteins involved in cell growth, stress responses and apoptosis. With diverse detection protocols, these microarrays enable high density profiling of lysate protein levels, phosphorylation and ubiquitination, and protein‐protein interactions in diverse experimental model systems, including human tumour cells in response to epidermal growth factor (EGF) and insulin treatment. One method involved the capture of in vitro biotin‐labeled lysate proteins, followed by their detection with dye‐labeled anti‐biotin antibody. False positive signals from associated proteins in complexes with the targets were reduced by chemical cleavage at cysteine residues with 2‐nitro‐5‐thiocyanatobenzoic acid (NTCB) prior to their capture on the array, and this also produced more uniformity of the dye signals for protein targets despite vast differences in their sizes. Transient changes in protein phosphorylation in EGF treated cells that were typically lost when processed by conventional methods were better preserved by chemical cleavage right at time of sample homogenization, and the chemically cleaved samples were stable for weeks without the need for refrigeration or freezing. Biotin‐labelling and subsequent detection of the antibody‐captured proteins on the arrays with a dye‐labeled anti‐biotin antibody reduced non‐specific background signals, allowed for a greater dynamic range of detection of up to 10,000‐fold, and enhanced discrimination of subtle changes in protein expression or phosphorylation. In conjunction with other detection protocols, such as the usage of dye‐labeled reporter antibodies for generic protein‐tyrosine phosphorylation in sandwich antibody microarrays (SAM format) or generic protein phosphorylation with nanoparticles such as pAMIGO (PAM format), it is also feasible to monitor changes in general phosphorylation of low abundance cell signalling proteins. The SAM format can also be adapted to identify target proteins that are subjected to other types of covalent modification such as ubiquitination and how these are altered when appropriate dye‐labelled covalent modification‐specific antibodies are deployed to probe the KAM‐900P and KAM‐1150E antibody microarrays. Furthermore, the SAM format has been used to monitor the interactions of complexed scaffolding, adaptor and chaperone proteins with signalling proteins that are captured on the antibody microarrays with specific, dye‐labelled reporter antibodies for the interacting proteins. Support or Funding Information This research was funded by Kinexus Bioinformatics Corporation, and LY was supported by a studentship award from the National Sciences and Engineering Research Council of Canada. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".