Spatiotemporal characterization of G protein β and γ subunit interactors via APEX2 labeling
Bibliographic record
Abstract
G protein-coupled receptors (GPCRs) represent a large family of membrane receptors involved in important physiological functions through regulation of myriad downstream signalling pathways.Many pathways work via heterotrimeric G proteins.In addition to the important role played by G subunits, recent work has described non canonical roles for G subunits in downstream signalling of GPCRs in organelles such as the nucleus, Golgi apparatus and mitochondria.Our lab has used tandem-affinity purification (TAP) to identify cytosolic and nuclear G-interacting proteins.Nonetheless, TAP and other methods to study protein interactions require them to be stable or require long incubation periods, missing transient and/or weak interactions.Furthermore, techniques that provide adequate temporal information often focus on one pathway at a time, requiring a large array of assays.The use of APEX2, a proximity-dependent labeling technique, provides both spatial and temporal information in endogenous protein expression level, allowing for more in-depth characterization of protein networks over time.This thesis describes the validation of APEX2-fused constructs, optimization of samples for LC-MS and subsequent proteins identified from our screens.Comparisons between TAP and APEX2 screens demonstrate various DNA/RNA binding proteins in HEK 293 cells, supporting the growing body of evidence for G in regulating transcription and suggests a novel role in protein synthesis.Proteins identified from different organelles also demonstrate the expanding roles of G, particularly in the nucleus.This work contributes to previously generated LC-MS data and provides a tool to study G signaling.Further experiments using fractionated samples will allow us to identify nuclear and cytoplasmic specific interactors, and stimulated conditions will enable us to observe proteome differences with receptor activation.v RSUM Les rcepteurs coupls aux protines G (GPCRs) reprsentent une grande famille de rcepteurs membranaires impliqus dans des fonctions physiologiques importantes par la rgulation de diverses voies de signalisation.Plusieurs de ces voies sont travers les protines G htrotrimrique.En plus des rles importants que jouent les sous-units G, des tudes rcentes dcrivent des rles pour les sous-units G en aval de la signalisation des GPCRs au niveau du noyau, l'Appareil de Golgi et les mitochondries.Notre laboratoire a prcdemment utilis la purification par affinit en tandem (TAP) pour identifier des protines cytosoliques et nuclaires qui interagissent avec G.Pourtant, TAP et autres mthodes pour l'tude des interactions protiques requirent qu'elles soient stables ou requirent de longues incubations ce qui vitent la dtection des interactions faibles et/ou transientes.De plus, les techniques qui fournissent adquatement l'information temporelle sont souvent axes sur une voie, et donc, requirent une multitude d'essais.L'utilisation de APEX2, une technique d'tiquetage dpendant de la proximit, fournit autant l'information temporelle que spatiale dans des concentrations endognes de protines, ce qui permet la caractrisation approfondie des rseaux protiques.Cette thse dcrit la validation des plasmides contenant le gne pour APEX2, l'optimisation des chantillons pour LC-MS et l'identification des protines provenant de nos essais.La comparaison de nos rsultats versus ceux de TAP dmontrent une varit de protines qui se lient l'ADN et l'ARN dans les cellules HEK 293, supportant les preuves pour G dans la rgulation de la transcription et suggre un rle novateur dans la synthse des protines.Les protines identifies provenant de diffrentes organelles dmontrent aussi la varit des rles de G, particulirement au niveau du noyau.Ces rsultats contribuent aux donnes de LC-MS prcdent et fournissent une mthode pour l'tude de la signalisation de G.De futures expriences qui utilisent le fractionnement cellulaire permettra vi l'observation des interactions spcifiques aux cytoplasme et au noyau, et des conditions stimules permettront de comparer les diffrences protomiques avec l'activation d'un rcepteur.vii ABBREVIATIONS 5-HT1F -5-hydroxytryptamine 1F 1-AR -1-adrenergic receptor 2-AR -2-adrenergic receptor 2-AR -2-adrenergic receptor AC -Adenylyl cyclase ACN -Acetonitrile AEBP1 -Adipocyte enhancer-binding protein AGS -Activator of G protein signaling AHSA1 -Activator of heat shock protein ATPase homolog 1 AP-1 -Activator protein-1 APEX -Ascorbate peroxidase AT1R -Angiotensin II type 1 receptor ATP -Adenosine triphosphate BSA -Bovine serum albumine CaM -Calmodulin binding peptide cAMPcyclic adenosine monophosphate CCT -T-complex protein 1 CHO -Chinese hamster
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".