Profiling Signaling Protein Expression, Modifications and Interactions with Multi‐dimensional Antibody Microarrays
Notice bibliographique
Résumé
Antibody microarrays permit the sensitive and semi‐quantitative analysis of the expression, covalent modification and interactions of proteins recovered from lysates of cells and tissues. At Kinexus, we have developed high content antibody microarrays that feature pan‐and phosphosite‐specific antibodies for tracking protein kinases, phosphatases and other low abundance cell signalling proteins for their expressions, covalent modifications and interactions with multiplex detection systems. Kinex™ KAM antibody microarrays with 880 printed antibodies were used to monitor protein levels, phosphorylation and interactions with combinations of different detection systems. One method involved capture of in vitro dye‐labeled proteins (e.g. with Cy3) from lysates from cells subjected to diverse treatments. Another method involved the detection of general changes in their protein phosphorylation with biotinylated pIMAGO stain and an anti‐biotin antibody that is labeled with a different dye (e.g. Cy5). Alterations in protein‐tyrosine phosphorylation were monitored with a dye‐labelled, generic phosphotyrosine‐specific PYK rabbit polyclonal antibody in a sandwich antibody microarray (SAM) format. The SAM technique was also used to explore the interactions of adapter, scaffolding and chaperone proteins with hundreds of potential target signal transduction proteins with dye‐labeled reporter antibodies for these highly interactive proteins. We used several human cancer cell lines (e.g. A431, HeLa, Jurkat, MCF7) subjected to diverse treatments (e.g. growth factors) to identify biomarkers of the actions of these agents. Reproducible results were obtained with as little as 25 μg of lysate protein, with a dynamic range of detection exceeding 6000‐fold, and a median error range for duplicates measurements of ±12%. Typically 10–15% of the proteins tracked with these arrays demonstrate perturbations exceeding 50%. More than a third of the leads from our antibody microarrays were confirmed by immunoblotting studies. The major limitation associated with validation by Western blotting was the much lower sensitivity with immunoblotting compared with antibody microarrays. We also explored the specific interactions of heat shock proteins, adapter proteins, 14‐3‐3 and calcium‐binding proteins with the antibody microarray captured lysate proteins from cancer cell lines. By combining these detection strategies, it was feasible to obtain over 7000 measurements from use of a single antibody microarray slide. The goal of our proteomics and bioinformatics studies is to use the experimental results from the application of these microarrays to map the architecture of signaling networks in a cell‐ or tissue‐specific manner. Such multi‐tiered microarray‐based analyses permit target‐directed identification of diverse regulatory protein changes in different experimental model systems with greater sensitivity, breadth, selectivity and economy when compared to any other competing proteomics methodologies. Support or Funding Information Supported by Kinexus Bioinformatics Corporation.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».