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Use of Novel ebBRET Biosensors for Comprehensive Signaling Profiling of One Hundred Therapeutically Relevant Human GPCRs

2021· article· en· W3168310094 on OpenAlexaff
Arturo Mancini, Charlotte Avet, Billy Breton, Christian Le Gouill, Alexander S. Hauser, Claire Normand, Florence Gross, Viktoriya Lukasheva, Mireille Hogue, Sandra Morissette, Eric B. Fauman, Jean‐Philippe Fortin, Stéphan Schann, Xavier Leroy, David E. Gloriam, Michel Bouvier

Bibliographic record

VenueThe FASEB Journal · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReceptor Mechanisms and Signaling
Canadian institutionsUniversité de MontréalInstitute for Research in Immunology and Cancer
FundersNovo Nordisk FondenLundbeckfonden
KeywordsG protein-coupled receptorReceptorFunctional selectivityEffectorFörster resonance energy transferSignal transductionG proteinComputational biologyChemistryBiologyRhodopsin-like receptorsCell biologyBiochemistryFluorescenceAgonist

Abstract

fetched live from OpenAlex

Functional selectivity is the ability of a given GPCR to engage multiple signaling pathways, with distinct ligands of the given receptor displaying different efficacies in engaging receptor‐coupled pathways. Full exploitation of functional selectivity in drug development will require an exhaustive description of the effectors that can be engaged by a given receptor, thus revealing receptor‐ and ligand‐specific signaling signatures. Here, we describe the signaling profiles of 100 therapeutically relevant human GPCRs in response to their endogenous (or prototypical) ligands. Profiling was performed with 15 pathway‐selective enhanced bystander bioluminescence resonance energy transfer (ebBRET) biosensors monitoring the activation of specific Gα proteins and βarrestins 1 and 2. The G protein biosensors represent a new generation of BRET‐based sensors that measure the translocation of G protein effectors to the plasma membrane with no need for modifying the G proteins or the receptors. Over 1,500 dose‑response curves were generated, revealing a great diversity in GPCR coupling selectivity. Our data highlight that the Gi family displayed the highest general coupling while Gs and G12/13 families were less frequently engaged by the receptors tested. Certain GPCRs (17%) showed greater selectivity, with coupling restricted to a single G protein subtype or members of the same G protein family. Others showed broader activation profiles; specifically, 39%, 35% and 9% of GPCRs tested coupled to members of two, three and all four G protein families, respectively. Somewhat surprisingly, some receptors showed G protein subtype selectivity among the members of the same family. Of note, over 50 novel GPCR/G protein couplings were uncovered. In addition to highlighting receptor G protein coupling preferences, our data revealed that 78% of GPCRs recruited βarrestin 1 and/or 2. For certain GPCRs, co‑expression of GRK2 augmented (and even exposed) βarrestin engagement. Finally, in addition to the signaling profiling application, we demonstrated the versatility and usefulness of our ebBRET biosensor platform to study constitutive GPCR activity/inverse agonism, ligand‐ and SNP‐induced biased signaling and cross‐talk systems pharmacology. Overall, this work complements and enriches the current body of data on GPCR effector coupling. Moreover, it presents innovative tools allowing to further explore novel GPCR pharmacology. The resources provided in this study, combined to other signaling profiling and omic‐scale datasets, will help deconvolute the complexities of GPCR biology and pharmacology and lead to innovative therapeutic exploitation of GPCRs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.104
GPT teacher head0.303
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2021
Admission routes1
Has abstractyes

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