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| Home > Publications database > Genetically Encoded Förster Resonance Energy Transfer-Based Biosensors Studied on the Single-Molecule Level > print |
| 001 | 850274 | ||
| 005 | 20240610121326.0 | ||
| 024 | 7 | _ | |a 10.1021/acssensors.8b00143 |2 doi |
| 024 | 7 | _ | |a pmid:29979038 |2 pmid |
| 024 | 7 | _ | |a WOS:000443103800006 |2 WOS |
| 024 | 7 | _ | |a altmetric:44770825 |2 altmetric |
| 037 | _ | _ | |a FZJ-2018-04316 |
| 082 | _ | _ | |a 540 |
| 100 | 1 | _ | |a Höfig, Henning |0 P:(DE-Juel1)165927 |b 0 |
| 245 | _ | _ | |a Genetically Encoded Förster Resonance Energy Transfer-Based Biosensors Studied on the Single-Molecule Level |
| 260 | _ | _ | |a Washington, DC |c 2018 |b ACS Publications |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1548836839_8840 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a Genetically encoded Förster resonance energy transfer (FRET)-based biosensors for the quantification of ligand molecules change the magnitude of FRET between two fluorescent proteins upon binding a target metabolite. When highly sensitive sensors are being designed, extensive sensor optimization is essential. However, it is often difficult to verify the ideas of modifications made to a sensor during the sensor optimization process because of the limited information content of ensemble FRET measurements. In contrast, single-molecule detection provides detailed information and higher accuracy. Here, we investigated a set of glucose and crowding sensors on the single-molecule level. We report the first comprehensive single-molecule study of FRET-based biosensors with reasonable counting statistics and identify characteristics in the single-molecule FRET histograms that constitute fingerprints of sensor performance. Hence, our single-molecule approach extends the toolbox of methods aiming to understand and optimize the design of FRET-based biosensors. |
| 536 | _ | _ | |a 551 - Functional Macromolecules and Complexes (POF3-551) |0 G:(DE-HGF)POF3-551 |c POF3-551 |f POF III |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef |
| 700 | 1 | _ | |a Otten, Julia |0 P:(DE-Juel1)165764 |b 1 |
| 700 | 1 | _ | |a Steffen, Victoria |0 P:(DE-Juel1)145517 |b 2 |
| 700 | 1 | _ | |a Pohl, Martina |0 P:(DE-Juel1)131522 |b 3 |
| 700 | 1 | _ | |a Boersma, Arnold J. |0 P:(DE-HGF)0 |b 4 |
| 700 | 1 | _ | |a Fitter, Joerg |0 P:(DE-HGF)0 |b 5 |e Corresponding author |
| 773 | _ | _ | |a 10.1021/acssensors.8b00143 |g p. acssensors.8b00143 |0 PERI:(DE-600)2843497-3 |n 8 |p 1462–1470 |t ACS sensors |v 3 |y 2018 |x 2379-3694 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/850274/files/acssensors.8b00143.pdf |y Restricted |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/850274/files/acssensors.8b00143.pdf?subformat=pdfa |x pdfa |y Restricted |
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| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l BioSoft – Fundamentals for future Technologies in the fields of Soft Matter and Life Sciences |1 G:(DE-HGF)POF3-550 |0 G:(DE-HGF)POF3-551 |2 G:(DE-HGF)POF3-500 |v Functional Macromolecules and Complexes |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF3 |
| 914 | 1 | _ | |y 2018 |
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| 920 | 1 | _ | |0 I:(DE-Juel1)ICS-5-20110106 |k ICS-5 |l Molekulare Biophysik |x 0 |
| 920 | 1 | _ | |0 I:(DE-Juel1)IBG-1-20101118 |k IBG-1 |l Biotechnologie |x 1 |
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| 981 | _ | _ | |a I:(DE-Juel1)IBI-6-20200312 |
| 981 | _ | _ | |a I:(DE-Juel1)ER-C-3-20170113 |
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