% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Hfig:850274,
      author       = {Höfig, Henning and Otten, Julia and Steffen, Victoria and
                      Pohl, Martina and Boersma, Arnold J. and Fitter, Joerg},
      title        = {{G}enetically {E}ncoded {F}örster {R}esonance {E}nergy
                      {T}ransfer-{B}ased {B}iosensors {S}tudied on the
                      {S}ingle-{M}olecule {L}evel},
      journal      = {ACS sensors},
      volume       = {3},
      number       = {8},
      issn         = {2379-3694},
      address      = {Washington, DC},
      publisher    = {ACS Publications},
      reportid     = {FZJ-2018-04316},
      pages        = {1462–1470},
      year         = {2018},
      abstract     = {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.},
      cin          = {ICS-5 / IBG-1},
      ddc          = {540},
      cid          = {I:(DE-Juel1)ICS-5-20110106 / I:(DE-Juel1)IBG-1-20101118},
      pnm          = {551 - Functional Macromolecules and Complexes (POF3-551)},
      pid          = {G:(DE-HGF)POF3-551},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:29979038},
      UT           = {WOS:000443103800006},
      doi          = {10.1021/acssensors.8b00143},
      url          = {https://juser.fz-juelich.de/record/850274},
}