Self-Assembled Gold Nanoparticle-Fluorescent Protein Conjugates as Platforms for Sensing Thiolate Compounds via Modulation of Energy Transfer Quenching.
Anshika KapurFadi AldeekXin JiMalak SafiWentao WangAda Del CidOliver SteinbockHedi MattoussiPublished in: Bioconjugate chemistry (2017)
The ability of Au and other metal nanostructures to strongly quench the fluorescence of proximal fluorophores (dyes and fluorescent proteins) has made AuNP conjugates attractive for use as platforms for sensor development based on energy transfer interactions. In this study, we first characterize the energy transfer quenching of mCherry fluorescent proteins immobilized on AuNPs via metal-histidine coordination, where parameters such as NP size and number of attached proteins are varied. Using steady-state and time-resolved fluorescence measurements, we recorded very high mCherry quenching, with efficiency reaching ∼95-97%, independent of the NP size or number of bound fluorophores (i.e., conjugate valence). We further exploited these findings to develop a solution phase sensing platform targeting thiolate compounds. Energy transfer (ET) was employed as a transduction mechanism to monitor the competitive displacement of mCherry from the Au surface upon the introduction of varying amounts of thiolates with different size and coordination numbers. Our results show that the competitive displacement of mCherry depends on the thiolate concentration, time of reaction, and type of thiol derivatives used. Further analysis of the PL recovery data provides a measure for the equilibrium dissociation constant (Kd-1) for these compounds. These findings combined indicate that the AuNP-fluorescent protein conjugates may offer a potentially useful platform for thiol sensing both in solution and in cell cultures.
Keyphrases
- energy transfer
- quantum dots
- sensitive detection
- cancer therapy
- living cells
- label free
- high throughput
- protein protein
- drug delivery
- binding protein
- electronic health record
- cell therapy
- reduced graphene oxide
- machine learning
- amino acid
- fluorescent probe
- molecular dynamics simulations
- electron transfer
- artificial intelligence
- big data
- mesenchymal stem cells
- gold nanoparticles