A Modular Biosensor Design for Quantitative Measurement of Free Nedd8.

DEN1 FRET Nedd8 and deneddylation biosensor luminescence nanoBiT neddylation

Journal

ACS sensors
ISSN: 2379-3694
Titre abrégé: ACS Sens
Pays: United States
ID NLM: 101669031

Informations de publication

Date de publication:
10 Sep 2024
Historique:
medline: 10 9 2024
pubmed: 10 9 2024
entrez: 10 9 2024
Statut: aheadofprint

Résumé

The objective of our study was to develop a genetically encoded biosensor for quantification of Nedd8, a post-translational modifier that regulates cellular signals through conjugation to other proteins. Perturbations in the balance of free (i.e., unconjugated) and conjugated Nedd8 caused by defects in Nedd8 enzymes or cellular stress are implicated in various diseases. Despite the biological and biomedical importance of Nedd8 dynamics, no method exists for direct quantification of free Nedd8, hindering the study of Nedd8 and activities of its associated enzymes. Genetically encoded biosensors are established as tools to study other dynamic systems, but limitations of current biosensor design methods make them poorly suited for free Nedd8 quantification. We have developed a modular method to design genetically encoded biosensors that employs a target binding domain and two reporter domains positioned on opposite sides of the target binding site. Target quantification is based on competition between target binding and the interaction of the reporter domains. We applied our design strategy to free Nedd8 quantification by developing a selective binder for free Nedd8 and combining it with fluorescent or split nanoluciferase reporters. Our sensors produced quantifiable and specific signals for free Nedd8 and enabled real-time monitoring of deneddylation by DEN1 with a physiological substrate. Our sensor design will be useful for high-throughput screening for deneddylation inhibitors, which have potential in treatment of cancers such as acute lymphoblastic leukemia. The modular design strategy can be extended to develop genetically encoded quantitative biosensors for other proteins of interest.

Identifiants

pubmed: 39253816
doi: 10.1021/acssensors.4c01130
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Zachary Wyatt Davis (ZW)

School of Natural Sciences, Black Hills State University, Spearfish, South Dakota 57799, United States.

Korbyn Coyle (K)

School of Natural Sciences, Black Hills State University, Spearfish, South Dakota 57799, United States.

Min Kyung Park (MK)

School of Natural Sciences, Black Hills State University, Spearfish, South Dakota 57799, United States.

Tara Oren (T)

School of Natural Sciences, Black Hills State University, Spearfish, South Dakota 57799, United States.

Teagen Hartley (T)

School of Natural Sciences, Black Hills State University, Spearfish, South Dakota 57799, United States.

Alyssa Umphlett (A)

School of Natural Sciences, Black Hills State University, Spearfish, South Dakota 57799, United States.

Jessilyn Monahan (J)

School of Natural Sciences, Black Hills State University, Spearfish, South Dakota 57799, United States.

Kylie Light (K)

School of Natural Sciences, Black Hills State University, Spearfish, South Dakota 57799, United States.

Kaylyn Hunter (K)

School of Natural Sciences, Black Hills State University, Spearfish, South Dakota 57799, United States.

Yun-Seok Choi (YS)

School of Natural Sciences, Black Hills State University, Spearfish, South Dakota 57799, United States.

Classifications MeSH