This work was supported by the Austrian Science Fund (FWF) projects P30214-N36, P32307-B, and by the Vienna Science and Technology Fund (WWTF) LS13-030.

<ol>
	<li>McKinney, S. A., D&#233;clais, A. -. C., Lilley, D. M. J., Ha, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Structural+dynamics+of+individual+holliday+junctions.">Structural dynamics of individual holliday junctions.</a> Nature Structural Biology. 10 (2), 93-97 (2002).</li><li>Wang, S., Vafabakhsh, R., Borschel, W. F., Ha, T., Nichols, C. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Structural+dynamics+of+potassium-channel+gating+revealed+by+single-molecule+FRET.">Structural dynamics of potassium-channel gating revealed by single-molecule FRET.</a> Nature Structural &amp; Molecular Biology. 23 (1), 31-36 (2015).</li><li>Hellenkamp, B., Wortmann, P., Kandzia, F., Zacharias, M., Hugel, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multidomain+structure+and+correlated+dynamics+determined+by+self-consistent+FRET+networks.">Multidomain structure and correlated dynamics determined by self-consistent FRET networks.</a> Nature Methods. 14 (2), 174-180 (2016).</li><li>Kilic, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-molecule+FRET+reveals+multiscale+chromatin+dynamics+modulated+by+HP1&#945;.">Single-molecule FRET reveals multiscale chromatin dynamics modulated by HP1&#945;.</a> Nature Communications. 9 (1), 235 (2018).</li><li>Stryer, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fluorescence+energy+transfer+as+a+spectroscopic+ruler.">Fluorescence energy transfer as a spectroscopic ruler.</a> Annual Review of Biochemistry. 47 (1), 819-846 (1978).</li><li>Wu, P. G., Brand, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Resonance+energy+transfer:+Methods+and+applications.">Resonance energy transfer: Methods and applications.</a> Analytical Biochemistry. 218 (1), 1-13 (1994).</li><li>Qiao, Y., Luo, Y., Long, N., Xing, Y., Tu, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-molecular+f&#246;rster+resonance+energy+transfer+measurement+on+structures+and+interactions+of+biomolecules.">Single-molecular f&#246;rster resonance energy transfer measurement on structures and interactions of biomolecules.</a> Micromachines. 12 (5), 492 (2021).</li><li>Malkusch, N., D&#246;rfler, T., Nagy, J., Eilert, T., Michaelis, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=smFRET+experiments+of+the+RNA+polymerase+II+transcription+initiation+complex.">smFRET experiments of the RNA polymerase II transcription initiation complex.</a> Methods. 120, 115-124 (2017).</li><li>Lee, J. -. B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-molecule+views+of+MutS+on+mismatched+DNA.">Single-molecule views of MutS on mismatched DNA.</a> DNA repair. 20, 82-93 (2014).</li><li>Phelps, C., Israels, B., Jose, D., Marsh, M. C., von Hippel, P. H., Marcus, A. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Using+microsecond+single-molecule+FRET+to+determine+the+assembly+pathways+of+T4+ssDNA+binding+protein+onto+model+DNA+replication+forks.">Using microsecond single-molecule FRET to determine the assembly pathways of T4 ssDNA binding protein onto model DNA replication forks.</a> Proceedings of the National Academy of Sciences of the United States of America. 114 (18), E3612-E3621 (2017).</li><li>Deindl, S., Zhuang, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Monitoring+conformational+dynamics+with+single-molecule+fluorescence+energy+transfer:+Applications+in+nucleosome+remodeling.">Monitoring conformational dynamics with single-molecule fluorescence energy transfer: Applications in nucleosome remodeling.</a> Methods in Enzymology. 513, 59-86 (2012).</li><li>Crawford, D. J., Hoskins, A. A., Friedman, L. J., Gelles, J., Moore, M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-molecule+colocalization+FRET+evidence+that+spliceosome+activation+precedes+stable+approach+of+5'+splice+site+and+branch+site.">Single-molecule colocalization FRET evidence that spliceosome activation precedes stable approach of 5' splice site and branch site.</a> Proceedings of the National Academy of Sciences of the United States of America. 110 (17), 6783-6788 (2013).</li><li>Wang, Y., Xiao, M., Li, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Heterogeneity+of+single+molecule+FRET+signals+reveals+multiple+active+ribosome+subpopulations.">Heterogeneity of single molecule FRET signals reveals multiple active ribosome subpopulations.</a> Proteins. 82 (1), 1-9 (2014).</li><li>Mori, T., Vale, R. D., Tomishige, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=How+kinesin+waits+between+steps.">How kinesin waits between steps.</a> Nature. 450 (7170), 750-754 (2007).</li><li>Huppa, J. B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=TCR-peptide-MHC+interactions+in+situ+show+accelerated+kinetics+and+increased+affinity.">TCR-peptide-MHC interactions in situ show accelerated kinetics and increased affinity.</a> Nature. 463 (7283), 963-967 (2010).</li><li>G&#246;hring, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Temporal+analysis+of+T-cell+receptor-imposed+forces+via+quantitative+single+molecule+FRET+measurements.">Temporal analysis of T-cell receptor-imposed forces via quantitative single molecule FRET measurements.</a> Nature Communications. 12 (1), 2502 (2021).</li><li>Hellenkamp, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Precision+and+accuracy+of+single-molecule+FRET+measurements-a+multi-laboratory+benchmark+study.">Precision and accuracy of single-molecule FRET measurements-a multi-laboratory benchmark study.</a> Nature Methods. 15 (9), 669 (2018).</li><li>Kapanidis, A. N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fluorescence-aided+molecule+sorting:+Analysis+of+structure+and+interactions+by+alternating-laser+excitation+of+single+molecules.">Fluorescence-aided molecule sorting: Analysis of structure and interactions by alternating-laser excitation of single molecules.</a> Proceedings of the National Academy of Sciences of the United States of America. 101 (24), 8936-8941 (2004).</li><li>Sakon, J. J., Weninger, K. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Detecting+the+conformation+of+individual+proteins+in+live+cells.">Detecting the conformation of individual proteins in live cells.</a> Nature Methods. 7 (3), 203-205 (2010).</li><li>McCann, J. J., Choi, U. B., Zheng, L., Weninger, K., Bowen, M. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optimizing+methods+to+recover+absolute+FRET+efficiency+from+immobilized+single+molecules.">Optimizing methods to recover absolute FRET efficiency from immobilized single molecules.</a> Biophysical Journal. 99 (3), 961-970 (2010).</li><li>Lee, N. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Accurate+FRET+measurements+within+single+diffusing+biomolecules+using+alternating-laser+excitation.">Accurate FRET measurements within single diffusing biomolecules using alternating-laser excitation.</a> Biophysical Journal. 88 (4), 2939-2953 (2005).</li><li>Asher, W. B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-molecule+FRET+imaging+of+GPCR+dimers+in+living+cells.">Single-molecule FRET imaging of GPCR dimers in living cells.</a> Nature Methods. 18 (4), 397-405 (2021).</li><li>Joo, C., Ha, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Single-molecule FRET with total internal reflection microscopy. (12), 1223-1237 (2012).</li><li>Joo, C., Ha, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Objective-type+total+internal+reflection+microscopy+(excitation)+for+single-molecule+FRET.">Objective-type total internal reflection microscopy (excitation) for single-molecule FRET.</a> Cold Spring Harbor Protocols. 11, 1189-1191 (2012).</li><li>Joo, C., Ha, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Objective-type+total+internal+reflection+microscopy+(emission)+for+single-molecule+FRET.">Objective-type total internal reflection microscopy (emission) for single-molecule FRET.</a> Cold Spring Harbor Protocols. 11, 1192-1194 (2012).</li><li>Allan, D. B., Caswell, T., van der Wel, C. M., Dimiduk, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Soft-matter/pims: PIMS v0.5. , (2020).</li><li>Anaconda Inc. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Miniconda. , (2021).</li><li>conda-forge community. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> The conda-forge project: community-based software distribution built on the conda package format and ecosystem. , (2015).</li><li>. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> JupyterLab Contributors Notebooks - JupyterLab documentation. , (2021).</li><li>Babcock, H., Sigal, Y. M., Zhuang, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+high-density+3D+localization+algorithm+for+stochastic+optical+reconstruction+microscopy.">A high-density 3D localization algorithm for stochastic optical reconstruction microscopy.</a> Optical Nanoscopy. 1 (6), (2012).</li><li>Gao, Y., Kilfoil, M. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Accurate+detection+and+complete+tracking+of+large+populations+of+features+in+three+dimensions.">Accurate detection and complete tracking of large populations of features in three dimensions.</a> Optics Express. 17 (6), 4685 (2009).</li><li>Schrangl, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> sdt-python: Python library for fluorescence microscopy data analysis (v17.1). , (2021).</li><li>Crocker, J. C., Grier, D. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Methods+of+digital+video+microscopy+for+colloidal+studies.">Methods of digital video microscopy for colloidal studies.</a> Journal of Colloid and Interface Science. 179 (1), 298-310 (1996).</li><li>Preibisch, S., Saalfeld, S., Schindelin, J., Tomancak, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Software+for+bead-based+registration+of+selective+plane+illumination+microscopy+data.">Software for bead-based registration of selective plane illumination microscopy data.</a> Nature Methods. 7 (6), 418-419 (2010).</li><li>Bradski, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+OpenCV+library.">The OpenCV library.</a> Dr. Dobb's Journal: Software Tools for the Professional Programmer. 25 (11), 120-123 (2000).</li><li>Allan, D. B., Caswell, T., Keim, N. C., van der Wel, C. M., Verweij, R. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Soft-matter/trackpy:+Trackpy+v0.5.0.">Soft-matter/trackpy: Trackpy v0.5.0.</a> Zenodo. , 4682814 (2021).</li><li>Killick, R., Fearnhead, P., Eckley, I. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optimal+detection+of+changepoints+with+a+linear+computational+cost.">Optimal detection of changepoints with a linear computational cost.</a> Journal of the American Statistical Association. 107 (500), 1590-1598 (2012).</li><li>Schrangl, L., G&#246;hring, J., Sch&#252;tz, G. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Kinetic+analysis+of+single+molecule+FRET+transitions+without+trajectories.">Kinetic analysis of single molecule FRET transitions without trajectories.</a> The Journal of Chemical Physics. 148 (12), 123328 (2018).</li><li>Santoso, Y., Torella, J. P., Kapanidis, A. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characterizing+single-molecule+FRET+dynamics+with+probability+distribution+analysis.">Characterizing single-molecule FRET dynamics with probability distribution analysis.</a> ChemPhysChem. 11 (10), 2209-2219 (2010).</li><li>Schrangl, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-molecule+FRET+analysis+software+(3.0).">Single-molecule FRET analysis software (3.0).</a> Zenodo. , (2021).</li><li>Nye, J. A., Groves, J. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Kinetic+control+of+histidine-tagged+protein+surface+density+on+supported+lipid+bilayers.">Kinetic control of histidine-tagged protein surface density on supported lipid bilayers.</a> Langmuir. 24 (8), 4145-4149 (2008).</li><li>Platzer, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Unscrambling+fluorophore+blinking+for+comprehensive+cluster+detection+via+photoactivated+localization+microscopy.">Unscrambling fluorophore blinking for comprehensive cluster detection via photoactivated localization microscopy.</a> Nature Communications. 11 (1), 4993 (2020).</li><li>Johnson, I., Spence, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> The molecular probes handbook: A guide to fluorescent probes and labeling technologies. , (2010).</li><li>Szalai, A. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Super-resolution+imaging+of+energy+transfer+by+intensity-based+STED-FRET.">Super-resolution imaging of energy transfer by intensity-based STED-FRET.</a> Nano Letters. 21 (5), 2296-2303 (2021).</li><li>Miyawaki, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fluorescent+indicators+for+Ca2++based+on+green+fluorescent+proteins+and+calmodulin.">Fluorescent indicators for Ca2+ based on green fluorescent proteins and calmodulin.</a> Nature. 388 (6645), 882-887 (1997).</li><li>Zhai, B., Zhai, S., Hao, R., Xu, J., Liu, Z. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+FRET-based+two-photon+probe+for+in+vivo+tracking+of+pH+during+a+traumatic+brain+injury+process.">A FRET-based two-photon probe for in vivo tracking of pH during a traumatic brain injury process.</a> New Journal of Chemistry. 43 (43), 17018-17022 (2019).</li></ol>

The authors declare no conflicts of interest.

This article details a pipeline for the automated recordings and quantitative analysis of smFRET data originating from mobile yet surface-tethered probe molecules. It complements the two predominant approaches to smFRET experiments, involving either surface-immobilized probes or probes diffusing in solution into and out of a confocal excitation volume17. It provides the correct FRET efficiency and the molecular positions as a function of time. It can therefore be used as input for specialized analysis programs, e.g., to quantify transition kinetics1, FRET histograms39, or two-dimensional diffusion22.
The software is released under a free and open-source license approved by the Open Source Initiative that grants the user the perpetual right to free usage, modification, and redistribution. Github was chosen as a development and distribution platform to make it as easy as possible to obtain the software and participate in the development process by reporting bugs or contributing code40. Written in Python, the software does not depend on proprietary components. The choice of Jupyter notebooks as user interfaces facilitates the inspection of data at every analysis step and allows for tailoring and extending the pipeline specifically for the experimental system at hand. The sdt-python library32 serves as the foundation and implements functionality to evaluate fluorescence microscopy data, such as single-molecule localization, diffusion analysis, fluorescence intensity analysis, color channel registration, colocalization analysis, and ROI handling.
In principle, single-particle tracking can be performed in one-, two- or three-dimensional systems. Here, the single-molecule analysis pipeline was tailored to the study of 2D mobile systems. This choice mirrors the availability of simple systems, such as planar-supported lipid bilayers (SLBs), to present mobile fluorescent probes. Such lipid bilayer systems are typically composed of two or more phospholipids moieties, where the bulk fraction determines the key physicochemical parameters of the SLB (such as phase and viscosity), and the minor fraction provides attachment sites for biomolecules. These attachment sites can be biotinylated phospholipids for avidin- or streptavidin-based protein platforms or nickel-NTA conjugated phospholipids for protein platforms with histidine tags41. The choice of the appropriate platform for linking proteins to the SLB depends on the scientific question. Readers can refer to the literature16,38,42 for examples of successfully employed strategies. The density of probes in the sample should be sufficiently low to avoid overlapping point spread functions; typically, less than 0.1 molecules per &#181;m2 are recommended. See the representative results section (in particular, Figure 6) for an example showing a suitable probe density. The analysis method is also applicable to single fluorescently labeled protein molecules diffusing in the plasma membrane of live cells.
One critical aspect of smFRET experiments is the production and characterization of the FRET probes themselves. When choosing fluorophores for a FRET pair, their F&#246;rster radius should match the expected inter-dye distances43. Dyes resistant to photobleaching are preferred as they yield long time traces. However, for elevated bleaching rates, one fluorophore species can be utilized to recognize multiemitter events originating from colocalized molecules via stepwise photobleaching analysis; see step 8.1.4 in the protocol section. Fluorophore pairs should be site-specifically and covalently attached to the molecules of interest, forming intra- or intermolecular FRET pairs.
Combining smFRET with other readily available techniques can increase its spatial resolution beyond the diffraction limit (via STED44). The smFRET tracking algorithm presented here widens the approach&#39;s applicability to new experimental settings and model systems. This includes studies of (i) kinetic changes in the stoichiometry of mobile biomolecules, (ii) dynamic association of mobile biomolecules, (iii) the rate of enzymatic reactions of freely diffusing reactants, and (iv) the kinetics of conformational changes of mobile biomolecules. The first two examples require model systems that show intermolecular FRET, i.e., donor and acceptor are conjugated to separate biomolecular entities of interest. The latter examples may make use of biosensors carrying donor and acceptor within the same molecular entity (intramolecular FRET).
Intramolecular FRET-based sensors can provide insight into intrinsic conformational changes of biomolecules1,2,3,4, conformational changes caused by endogenous or external force load (molecular force sensors16), or ion concentrations in the nano-environment such as calcium45 and pH46. Depending on the model system and the preferred anchoring platform, such smFRET events can either be tracked in 2D or 3D: (i) planar tracking of smFRET events can be employed for the quantification of receptor-ligand interaction times within a plasma membrane, the association of membrane-anchored signal amplification cascades, and the stoichiometry changes of surface receptors; (ii) volume tracking of smFRET events can be used for any intra- or intermolecular FRET probes in living cells or in in vitro reconstituted systems.
The smFRET tracking method was developed mainly with intramolecular FRET probes in mind. These probes feature a fixed and well-known number of fluorescent labels, a fact that was exploited to reject data from agglomerated and incorrectly synthesized (e.g., incompletely labeled) molecules, as well as from probes where one of the fluorophores has been photobleached. However, by adjusting the filtering steps, the method can also be applied to intermolecular FRET probes. For instance, instead of accepting only molecules featuring a single donor and a single acceptor fluorophore, one could examine the spatial trajectories of donor and acceptor dyes and select, for example, for co-diffusing donor-acceptor trajectories.
As the 3D-DAOSTORM algorithm has support for determining a signal&#39;s position along the optical axis via the astigmatism due to a cylindrical lens in the emission beam path, 3D experiments could be easily integrated into the analysis pipeline. In this case, the acceptor signal upon acceptor excitation would serve to determine the stoichiometry and the axial position. The analysis software can also be employed to evaluate data from experiments featuring immobilized probes by utilizing its large degree of automation and filtering schemes. In fact, smFRET efficiency datasets from Holliday junctions immobilized on gel-phase bilayers38 were analyzed using an early version of the software.

F&#246;rster resonance energy transfer (FRET) has been a major driver in molecular biological and biophysical research, as it allows the investigation of processes at sub-nanometer resolution. As the efficiency of energy transfer between donor and acceptor fluorophores strongly depends on the inter-dye distance in the sub-nanometer to nanometer range, it has been effectively used as a spectroscopic ruler to explore static and dynamic conformation of biomolecules1,2,3,4. Additionally, the FRET phenomenon has been widely used for colocalization studies of membrane-associated and intracellular proteins on a bulk level5,6. In the last two decades, the method was adapted for monitoring smFRET events7, which helped to substantially increase temporal and spatial resolution and resolved even rare subpopulations in heterogeneous samples. Equipped with these techniques, unique insights were gained into the dynamics of molecular machinery such as the transcript processing rate of RNA polymerase II8, replication speed of DNA polymerases9,10, nucleosome translocation rate11, transcript splicing and stalling rate of assembled spliceosomes12, the activity of ribosomal subpopulations13, and the walking speed of kinesin motors14, to name a few. Receptor-ligand interaction durations15 and molecular forces16 have been quantified.
Intensity-based smFRET studies typically rely on sensitized emission to measure FRET efficiency: a beam splitter in the emission path spatially separates light originating from donor and acceptor fluorophores upon donor excitation, allowing for the quantification of individual fluorescence intensities. The efficiency can subsequently be calculated as the fraction of photons emitted by the acceptor with respect to the total photon count17. In addition, acceptor excitation following donor excitation (ALEX) permits measurement of the stoichiometry of the FRET events, aiding in the discrimination between true low FRET signals from signals arising, e.g., from probes featuring a photobleached acceptor fluorophore18.
Single-molecule FRET experiments are commonly carried out in one of two ways. First, a small region in the sample volume is illuminated using a confocal microscope. Single probe molecules in solution are excited when they happen to diffuse within the focal volume. With this technique, fast photon-counting detectors can be used, enabling sub-microsecond time resolution. Second, probes are specifically immobilized on surfaces and monitored via widefield microscopy, often using total internal reflection (TIR) configuration to minimize background fluorescence. Probe immobilization allows for much longer recording times than using the first approach. In addition, the larger field of view permits the monitoring of multiple probes in parallel. The need for a camera makes this method slow compared to the one described above. Time resolution is limited to the millisecond to second range.
If long time traces are required, e.g., for studying dynamic processes on a millisecond to second time scale, the first method is not applicable, as the fluorescence bursts are typically too short. The second approach fails whenever immobilization is not feasible, e.g., in live-cell experiments featuring probes diffusing within the cell membrane. Furthermore, it has been observed that biological model systems can vary their response dramatically depending on the mobility of the contacted surface16.
While combined smFRET and single-particle tracking experiments recording mobile FRET probes have been performed in the past19, there is no publicly available software for the evaluation of the data. This prompted the development of a new analysis platform, which allows for the determination of multiple properties of mobile fluorescent probes, including smFRET efficiency and stoichiometry, positions with sub-pixel accuracy, and fluorescence intensities as functions of time. Methods for filtering the resulting traces by examining stepwise bleaching behavior, nearest-neighbor distances, emission intensities, and other traits were established to exclusively choose correctly synthesized and functional single-probe molecules. The software also supports experimental and analytical techniques recently agreed upon in a multilaboratory study to produce reliable, quantitative smFRET data17. In particular, the implementation adheres to the validated procedures for the calculation of FRET efficiency and stoichiometry. Fluorescence intensities upon donor excitation in the donor emission channel IDD and acceptor emission channel IDA are used for the calculation of the apparent FRET efficiency Eapp using Eq (1).
<img alt="Equation 1" src="/files/ftp_upload/63124/63124eq01.jpg" /> (1)
With the help of the fluorescence intensity in the acceptor emission channel upon acceptor excitation IAA, the apparent stoichiometry is calculated using Eq (2).
<img alt="Equation 2" src="/files/ftp_upload/63124/63124eq02.jpg" /> (2)
The FRET efficiency E and the stoichiometry S can be derived from Eapp and Sapp by considering four correction factors.
<img alt="Equation 3" src="/files/ftp_upload/63124/63124eq03.jpg" />
&#945; describes the leakage of donor fluorescence into the acceptor emission channel and can be determined using a sample containing only donor fluorophores or by analyzing parts of trajectories where the acceptor has been bleached.&#160;&#948; corrects for the direct excitation of the acceptor by the donor excitation light source and can be measured using a sample with only acceptor fluorophores or by analyzing parts of trajectories where the donor has been bleached.
<img alt="Equation 4" src="/files/ftp_upload/63124/63124eq04.jpg" />.
&#947; scales IDD to rectify diverging detection efficiencies in donor and acceptor emission channels and different quantum efficiencies of the fluorophores. The factor can be computed by analyzing the increase in donor intensity upon acceptor bleaching in trajectories with high FRET efficiencies20 or by studying a sample featuring multiple discrete FRET states.
<img alt="Equation 5" src="/files/ftp_upload/63124/63124eq05.jpg" />
&#946; scales IAA to correct for disparate efficiencies of donor and acceptor excitation. If &#947; was determined via acceptor bleaching analysis, &#946; could be calculated from a sample of known donor-to-acceptor ratio21. Otherwise, the multi-state FRET sample also yields &#946;.
Together, the corrections allow the calculation of the corrected FRET efficiency using Eq (3).
<img alt="Equation 6" src="/files/ftp_upload/63124/63124eq06.jpg" /> (3)
and the corrected stoichiometry using Eq (4).
<img alt="Equation 7" src="/files/ftp_upload/63124/63124eq07.jpg" /> (4)
Ideally, the corrected stoichiometry for a 1:1 donor-to-acceptor ratio gives S = 0.5. In practice, a reduced signal-to-noise ratio produces a spread of the measured values of S, hampering the discrimination from donor-only signals (S = 1) and acceptor-only signals (S = 0). The resulting time traces can be used as input for a more detailed analysis of the single-molecule trajectories to obtain information such as spatiotemporal force profiles16, the mobility of the single-molecule events22, or transition kinetics between different states1.
The following protocol describes experimental parameters and procedures for smFRET tracking experiments, as well as the working principle behind data analysis using the newly developed software suite. For the acquisition of experimental data, it is recommended to use a microscopy setup meeting the following requirements: i) capability of detecting the emission of single dye molecules; ii) widefield illumination: in particular for live-cell experiments, total internal reflection (TIR23,24,25) configuration is recommended; iii) spatial separation of emission light according to wavelength such that donor and acceptor fluorescence is projected onto different regions of the same camera chip25 or different cameras; iv) modulation of light sources for donor and acceptor excitation with millisecond precision, e.g., using directly modulatable lasers or modulation via acousto-optic modulators. This permits stroboscopic illumination to minimize photobleaching of fluorophores as well as alternating excitation to determine stoichiometries; v) output of one file per recorded image sequence in a format that can be read by the PIMS Python package26. In particular, multipage TIFF files are supported.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>1,2-dioleoyl-sn-glycero-3-[(N-(5-amino-1-carboxypentyl)iminodiacetic acid)succinyl] (nickel salt) (Ni-NTA-DOGS)</td>
			<td>Avanti Polar Lipids</td>
			<td>790404P</td>
			<td></td>
		</tr>
		<tr>
			<td>1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC)</td>
			<td>Avanti Polar Lipids</td>
			<td>850375P</td>
			<td></td>
		</tr>
		<tr>
			<td>1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (POPC)</td>
			<td>Avanti Polar Lipids</td>
			<td>850457P</td>
			<td></td>
		</tr>
		<tr>
			<td>&#945; Plan-FLUAR 100x/1.45 oil objective</td>
			<td>Zeiss</td>
			<td>000000-1084-514</td>
			<td></td>
		</tr>
		<tr>
			<td>Axio Observer microscope body</td>
			<td>Zeiss</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Bandpass filter</td>
			<td>Chroma Technology Corp</td>
			<td>ET570/60m</td>
			<td>donor emission filter</td>
		</tr>
		<tr>
			<td>Bandpass filter</td>
			<td>Chroma Technology Corp</td>
			<td>ET675/50m</td>
			<td>acceptor emission filter</td>
		</tr>
		<tr>
			<td>conda-forge</td>
			<td>conda-forge community</td>
			<td></td>
			<td>community-maintaned Python package repository for Anaconda/miniconda</td>
		</tr>
		<tr>
			<td>Coverslips 60 mm x 24 mm #1.5</td>
			<td>MENZEL</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Dichroic mirror</td>
			<td>Semrock Inc</td>
			<td>FF640-FDi01-25&#215;36</td>
			<td>separation of donor and acceptor emission</td>
		</tr>
		<tr>
			<td>Dichroic mirror (quad band)</td>
			<td>Semrock Inc</td>
			<td>Di01-R405/488/532/635-25&#215;36</td>
			<td>separation of excitation and emission light</td>
		</tr>
		<tr>
			<td>DPBS</td>
			<td>Sigma-Aldrich</td>
			<td>D8537</td>
			<td></td>
		</tr>
		<tr>
			<td>FCS</td>
			<td>Sigma-Aldrich</td>
			<td>F7524</td>
			<td>for imaging buffer</td>
		</tr>
		<tr>
			<td>fret-analysis</td>
			<td>Sch&#252;tz group at TU Wien</td>
			<td></td>
			<td>Python package for smFRET data analysis; version 3</td>
		</tr>
		<tr>
			<td>Fura-2 AM</td>
			<td>Thermo Fisher Scientific</td>
			<td>11524766</td>
			<td></td>
		</tr>
		<tr>
			<td>HBSS</td>
			<td>Sigma-Aldrich</td>
			<td>H8264</td>
			<td>for imaging buffer</td>
		</tr>
		<tr>
			<td>iBeam Smart 405-S 405 nm laser</td>
			<td>Toptica Photonics AG</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>iXon Ultra 897 EMCCD camera</td>
			<td>Andor Technology Ltd</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Lab-Tek chambers (8 wells)</td>
			<td>Thermo Fisher Scientific</td>
			<td>177402PK</td>
			<td>for sample preparation and imaging</td>
		</tr>
		<tr>
			<td>Millenia Prime 532 nm laser</td>
			<td>Spectra Physics</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>miniconda</td>
			<td>Anaconda Inc.</td>
			<td></td>
			<td>Python 3 distribution. Min. version: 3.7</td>
		</tr>
		<tr>
			<td>Monovalent streptavidin (plasmids for bacterial expression)</td>
			<td>Addgene</td>
			<td>20860 &#38; 20859</td>
			<td></td>
		</tr>
		<tr>
			<td>OBIS 640 nm laser</td>
			<td>Coherent Inc</td>
			<td>1185055</td>
			<td></td>
		</tr>
		<tr>
			<td>Optosplit II</td>
			<td>Cairn Research</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Ovalbumin</td>
			<td>Sigma-Aldrich</td>
			<td>A5253</td>
			<td>for imaging buffer</td>
		</tr>
		<tr>
			<td>Plasma cleaner</td>
			<td>Harrick Plasma</td>
			<td>PDC-002</td>
			<td></td>
		</tr>
		<tr>
			<td>sdt-python</td>
			<td>Sch&#252;tz group at TU Wien</td>
			<td></td>
			<td>Python library for data analysis; version 17</td>
		</tr>
		<tr>
			<td>TetraSpek bead size kit</td>
			<td>Thermo Fisher Scientific</td>
			<td>T14792</td>
			<td>Randomly distributed, immobilized fiducial markers for image registration</td>
		</tr>
		<tr>
			<td>USC500TH Ultrasound bath</td>
			<td>VWR</td>
			<td></td>
			<td>for SUV formation</td>
		</tr>
	</tbody>
</table>

automated two-dimensional spatiotemporal analysis of mobile single-molecule fret probes

Single-molecule F&#246;rster resonance energy transfer (smFRET) is a versatile technique reporting on distances in the sub-nanometer to nanometer range. It has been used in a wide range of biophysical and molecular biological experiments, including the measurement of molecular forces, characterization of conformational dynamics of biomolecules, observation of intracellular colocalization of proteins, and determination of receptor-ligand interaction times. In a widefield microscopy configuration, experiments are typically performed using surface-immobilized probes. Here, a method combining single-molecule tracking with alternating excitation (ALEX) smFRET experiments is presented, permitting the acquisition of smFRET time traces of surface-bound, yet mobile probes in plasma membranes or glass-supported lipid bilayers. For the analysis of recorded data, an automated, open-source software collection was developed supporting (i) the localization of fluorescent signals, (ii) single-particle tracking, (iii) determination of FRET-related quantities including correction factors, (iv) stringent verification of smFRET traces, and (v) intuitive presentation of the results. The generated data can conveniently be used as input for further exploration via specialized software, e.g., for the assessment of the diffusional behavior of probes or the investigation of FRET transitions.

A variety of low- and high-level information can be extracted from smFRET tracks depending on the scientific question of the experiment. Here, examples of analysis pipelines with analog and digital probes are presented: a peptide-based molecular force sensor16 and a DNA probe with stochastic switching of its conformation38, respectively. Refer to Figure 5 for the design and working principle of these probes.
After the localization and tracking algorithms have been executed as described in the protocol, the package offers multiple data visualization tools to optimize the initial parameters and subsequent filter steps: (i) visualization of individual smFRET events, (ii) optional image segmentation to analyze data in certain regions of interests, (iii) monitoring of filter steps via FRET efficiency vs. stoichiometry (E-S) plots. The visualization of the single-molecule data is presented in Figure 6.
Finally, the filtered FRET events are represented by an E-S plot and a FRET efficiency histogram (Figure 4). The E-S plot is a useful tool for optimizing the aforementioned filtering steps and investigating the final result. Partially bleached or incompletely labeled FRET sensors can be excluded by their stoichiometry value. Mobility parameters can be investigated by plotting an individual trajectory path in an x-y plot (Figure 6) or a mean square displacement (MSD) plot (Figure 4). The first method is especially useful for discriminating mobile from immobilized events, while the latter is used to calculate the diffusion coefficient.
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/63124/63124fig04.jpg" /> 
Figure 4: Exemplary output. (A) The FRET efficiency is plotted versus stoichiometry (E-S plot) for a population of the molecular force sensor (left panel) decorating a glass-supported lipid bilayer and strained by a T cell. Only one population cloud is visible. The respective histogram of FRET efficiencies exemplifies the difference between a force sensor population in presence and absence of cells (middle panel). No shift to lower FRET efficiencies of the sensor population in presence of T cells can be observed, indicating little to no force-dependent stretching of the sensor module. The MSD plot of these experimental conditions confirms that the force sensor population beneath a T cell moves considerably slower than their unbound counterparts (right panel). (B) The same analysis was performed with Holliday junction DNA sensor decorating a glass-supported fluid lipid bilayer. The E-S plot clearly shows two populations, which are also apparent in the FRET efficiency histogram. The MSD plot indicates the presence of one fast-moving sensor population. Abbreviations: FRET = F&#246;rster resonance energy transfer; MSD = mean square displacement. <a href="https://www.jove.com/files/ftp_upload/63124/63124fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/63124/63124fig05.jpg" /> 
Figure 5: Design and working principle of intramolecular FRET probes. (A) Analog peptide sensor for quantification of mechanical molecular forces. The donor and acceptor fluorophores are covalently attached to either end of the peptide backbone. The sensor module is site-specifically attached to a specific ligand, which in turn binds a cell-resident surface receptor of interest (here, an antibody fragment specifically recognizing the beta chain of the T cell receptor). Upon receptor-ligand binding, force is exerted, and the sensor module extends and eventually recoils after bond cleavage. This panel is modified from 16. (B) Digital DNA sensor for quantification of FRET transitions. The FRET sensor is composed of four DNA strands forming a Holliday junction. The donor and acceptor fluorophore are covalently attached to two strands. Holliday junctions frequently switch their conformation depending on the surrounding buffer conditions. The stochastic switching of these conformations can be monitored by quantifying the FRET efficiency of individual probes. Abbreviations: TCR = T cell receptor; FRET = F&#246;rster resonance energy transfer. <a href="https://www.jove.com/files/ftp_upload/63124/63124fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/63124/63124fig06.jpg" /> 
Figure 6: Examples of localization and tracking of FRET probes. (A) The FRET efficiency and stoichiometry of individual events are calculated by quantifying the intensity of the donor fluorophore upon donor excitation (D &#8594; D), the acceptor fluorophore upon donor excitation (D &#8594; A), and the acceptor fluorophore upon acceptor excitation (A &#8594; A). Nearest neighbor filtering prevents bias by overlapping point spread functions of close emitters. Image segmentation allows the user to choose certain smFRET events localized within an area of interest (e.g., a cell or a micropattern). As an example of image segmentation, T cells were stained with Fura-2 (displayed on the left) and subjected to adaptive thresholding to identify the cell edges (orange dotted line). Scale bars = 5 &#181;m. (B) smFRET trajectories using the molecular force sensor. Individual trajectories can be plotted in the x-y plane, visualizing their diffusion behavior and localization (left panel). Furthermore, each trajectory&#39;s intensities can be plotted over time to identify FRET transitions or bleaching steps (middle panel shows the red trajectory from the left panel). The resulting FRET efficiency and stoichiometry can be visualized similarly (right panel). (C) smFRET trajectories using the Holliday junction DNA sensor. HBSS + 12 mM MgCl2 was used as a buffer during the measurements. Apart from the apparent acceptor bleaching step near the sequence end of these examples, the frequency of FRET transitions for each sensor can be determined. The Holliday junctions switch their conformation with a high frequency, whereas the molecular force sensor does not exhibit FRET transitions. This information makes it possible to adjust the experimental conditions, such as the delay between the frames, to increase or reduce the number of observed transitions. Abbreviations: FRET = F&#246;rster resonance energy transfer; smFRET = single-molecule FRET; HBSS = Hank&#39;s balanced salt solution. <a href="https://www.jove.com/files/ftp_upload/63124/63124fig06large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplemental Information: Localization and tracking of single molecules (01. Tracking.ipynb). <a href="https://www.jove.com/files/ftp_upload/63124/si.pdf" target="_blank">Please click here to download this File.</a>

Watch this Scientific Journal Video about Automated Two-dimensional Spatiotemporal Analysis of Mobile Single-molecule FRET Probes at JoVE.com

Automated Two-dimensional Spatiotemporal Analysis of Mobile Single-molecule FRET Probes

This article presents a method for spatiotemporal analysis of mobile, single-molecule F&#246;rster resonance energy transfer (smFRET)-based probes using widefield fluorescence microscopy. The newly developed software toolkit allows the determination of smFRET time traces of moving probes, including the correct FRET efficiency and the molecular positions, as functions of time.

Single-molecule F&#246;rster resonance energy transfer (smFRET) is a versatile technique reporting on distances in the sub-nanometer to nanometer range. ...

automated-two-dimensional-spatiotemporal-analysis-mobile-single

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JoVE Journal

Bioengineering

2.4K Views.  TU Wien. This article presents a method for spatiotemporal analysis of mobile, single-molecule Förster resonance energy transfer (smFRET)-based probes using widefield fluorescence microscopy. The newly developed software toolkit allows the determination of smFRET time traces of moving probes, including the correct FRET efficiency and the molecular positions, as functions of time.

Video: Automated Two-dimensional Spatiotemporal Analysis of Mobile Single-molecule FRET Probes

Creating Two-Dimensional Patterned Substrates for Protein and Cell Confinement

Microcontact printing provides a rapid, highly reproducible method for the creation of well-defined patterned substrates.1 While microcontact printing can be employed to directly print a large number of molecules, including proteins,2 DNA,3 and silanes,4 the formation of self-assembled monolayers (SAMs) from long chain alkane thiols on gold provides a simple way to confine proteins and cells to specific patterns containing adhesive and resistant regions. This confinement can be used to control cell morphology and is useful for examining a variety of questions in protein and cell biology. Here, we describe a general method for the creation of well-defined protein patterns for cellular studies.5 This process involves three steps: the production of a patterned master using photolithography, the creation of a PDMS stamp, and microcontact printing of a gold-coated substrate. Once patterned, these cell culture substrates are capable of confining proteins and/or cells (primary cells or cell lines) to the pattern.
The use of self-assembled monolayer chemistry allows for precise control over the patterned protein/cell adhesive regions and non-adhesive regions; this cannot be achieved using direct protein stamping. Hexadecanethiol, the long chain alkane thiol used in the microcontact printing step, produces a hydrophobic surface that readily adsorbs protein from solution. The glycol-terminated thiol, used for backfilling the non-printed regions of the substrate, creates a monolayer that is resistant to protein adsorption and therefore cell growth.6 These thiol monomers produce highly structured monolayers that precisely define regions of the substrate that can support protein adsorption and cell growth. As a result, these substrates are useful for a wide variety of applications from the study of intercellular behavior7 to the creation of microelectronics.8
While other types of monolayer chemistry have been used for cell culture studies, including work from our group using trichlorosilanes to create patterns directly on glass substrates,9 patterned monolayers formed from alkane thiols on gold are straight-forward to prepare. Moreover, the monomers used for monolayer preparation are commercially available, stable, and do not require storage or handling under inert atmosphere. Patterned substrates prepared from alkane thiols can also be recycled and reused several times, maintaining cell confinement.10

Self-assembled monolayers (SAMs) formed from long chain alkane thiols on gold provide well-defined substrates for the formation of protein patterns and cell confinement. Microcontact printing of hexadecanethiol using a polydimethylsiloxane (PDMS) stamp followed by backfilling with a glycol-terminated alkane thiol monomer produces a pattern where protein and cells adsorb only to the stamped hexadecanethiol region.

Microcontact printing provides a rapid, highly reproducible method for the creation of well-defined patterned substrates.1  While microcontact printing ...

Multiplexed Single-molecule Force Proteolysis Measurements Using Magnetic Tweezers

The generation and detection of mechanical forces is a ubiquitous aspect of cell physiology, with direct relevance to cancer metastasis1, atherogenesis2 and wound healing3. In each of these examples, cells both exert force on their surroundings and simultaneously enzymatically remodel the extracellular matrix (ECM). The effect of forces on ECM has thus become an area of considerable interest due to its likely biological and medical importance4-7.
	Single molecule techniques such as optical trapping8, atomic force microscopy9, and magnetic tweezers10,11 allow researchers to probe the function of enzymes at a molecular level by exerting forces on individual proteins. Of these techniques, magnetic tweezers (MT) are notable for their low cost and high throughput. MT exert forces in the range of ~1-100 pN and can provide millisecond temporal resolution, qualities that are well matched to the study of enzyme mechanism at the single-molecule level12. Here we report a highly parallelizable MT assay to study the effect of force on the proteolysis of single protein molecules. We present the specific example of the proteolysis of a trimeric collagen peptide by matrix metalloproteinase 1 (MMP-1); however, this assay can be easily adapted to study other substrates and proteases.

In this article we describe the use of magnetic tweezers to study the effect of force on enzymatic proteolysis at the single molecule level in a highly parallelizable manner.

The  generation and detection of mechanical forces is a ubiquitous aspect of cell physiology,  with direct relevance to cancer metastasis1, atherogenesis2 ...

Quantitative FRET (F&#246;rster Resonance Energy Transfer) Analysis for SENP1 Protease Kinetics Determination

Reversible posttranslational modifications of proteins with ubiquitin or ubiquitin-like proteins (Ubls) are widely used to dynamically regulate protein activity and have diverse roles in many biological processes. For example, SUMO covalently modifies a large number or proteins with important roles in many cellular processes, including cell-cycle regulation, cell survival and death, DNA damage response, and stress response 1-5. SENP, as SUMO-specific protease, functions as an endopeptidase in the maturation of SUMO precursors or as an isopeptidase to remove SUMO from its target proteins and refresh the SUMOylation cycle 1,3,6,7.
The catalytic efficiency or specificity of an enzyme is best characterized by the ratio of the kinetic constants, kcat/KM. In several studies, the kinetic parameters of SUMO-SENP pairs have been determined by various methods, including polyacrylamide gel-based western-blot, radioactive-labeled substrate, fluorescent compound or protein labeled substrate 8-13. However, the polyacrylamide-gel-based techniques, which used the "native" proteins but are laborious and technically demanding, that do not readily lend themselves to detailed quantitative analysis. The obtained kcat/KM from studies using tetrapeptides or proteins with an ACC (7-amino-4-carbamoylmetylcoumarin) or AMC (7-amino-4-methylcoumarin) fluorophore were either up to two orders of magnitude lower than the natural substrates or cannot clearly differentiate the iso- and endopeptidase activities of SENPs.
Recently, FRET-based protease assays were used to study the deubiquitinating enzymes (DUBs) or SENPs with the FRET pair of cyan fluorescent protein (CFP) and yellow fluorescent protein (YFP) 9,10,14,15. The ratio of acceptor emission to donor emission was used as the quantitative parameter for FRET signal monitor for protease activity determination. However, this method ignored signal cross-contaminations at the acceptor and donor emission wavelengths by acceptor and donor self-fluorescence and thus was not accurate.
We developed a novel highly sensitive and quantitative FRET-based protease assay for determining the kinetic parameters of pre-SUMO1 maturation by SENP1. An engineered FRET pair CyPet and YPet with significantly improved FRET efficiency and fluorescence quantum yield, were used to generate the CyPet-(pre-SUMO1)-YPet substrate 16. We differentiated and quantified absolute fluorescence signals contributed by the donor and acceptor and FRET at the acceptor and emission wavelengths, respectively. The value of kcat/KM was obtained as (3.2 &plusmn; 0.55) x107 M-1s-1 of SENP1 toward pre-SUMO1, which is in agreement with general enzymatic kinetic parameters. Therefore, this methodology is valid and can be used as a general approach to characterize other proteases as well.

Quantitative FRET F&#246;rster Resonance Energy Transfer Analysis for SENP1 Protease Kinetics Determination

A novel method involving quantitative analysis of FRET (F&ouml;rster Resonance Energy Transfer) signals is described for studying enzyme kinetics. KM and kcat were obtained for the hydrolysis of the catalytic domain of SENP1 (SUMO/Sentrin specific protease 1) to pre-SUMO1 (Small Ubiquitin-like MOdifier). The general principles of this quantitative-FRET-based protease kinetic study can be applied to other proteases.

Reversible posttranslational modifications of proteins with ubiquitin or ubiquitin-like proteins (Ubls) are widely used to dynamically regulate protein ...

Investigating Receptor-ligand Systems of the Cellulosome with AFM-based Single-molecule Force Spectroscopy

Cellulosomes are discrete multienzyme complexes used by a subset of anaerobic bacteria and fungi to digest lignocellulosic substrates. Assembly of the enzymes onto the noncatalytic scaffold protein is directed by interactions among a family of related receptor-ligand pairs comprising interacting cohesin and dockerin modules. The extremely strong binding between cohesin and dockerin modules results in dissociation constants in the low picomolar to nanomolar range, which may hamper accurate off-rate measurements with conventional bulk methods. Single-molecule force spectroscopy (SMFS) with the atomic force microscope measures the response of individual biomolecules to force, and in contrast to other single-molecule manipulation methods (i.e.&#160;optical tweezers), is optimal for studying high-affinity receptor-ligand interactions because of its ability to probe the high-force regime (&#62;120 pN). Here we present our complete protocol for studying cellulosomal protein assemblies at the single-molecule level. Using a protein topology derived from the native cellulosome, we worked with enzyme-dockerin and carbohydrate binding module-cohesin (CBM-cohesin) fusion proteins, each with an accessible free thiol group at an engineered cysteine residue. We present our site-specific surface immobilization protocol, along with our measurement and data analysis procedure for obtaining detailed binding parameters for the high-affinity complex. We demonstrate how to quantify single subdomain unfolding forces, complex rupture forces, kinetic off-rates, and potential widths of the binding well. The successful application of these methods in characterizing the cohesin-dockerin interaction responsible for assembly of multidomain cellulolytic complexes is further described.

Cellulosomes are multienzyme complexes designed for digesting cellulose. AFM-based SMFS was used to study the mechanical properties and folding configuration of cellulosome-associated protein assemblies. We present a complete workflow for protein immobilization, data acquisition, and data analysis to study the interactions of individual receptor-ligand complexes involved in cellulosome assembly.

Cellulosomes are discrete multienzyme complexes used by a subset of anaerobic bacteria and fungi to digest lignocellulosic substrates. Assembly of the ...

High-resolution Spatiotemporal Analysis of Receptor Dynamics by Single-molecule Fluorescence Microscopy

Single-molecule microscopy is emerging as a powerful approach to analyze the behavior of signaling molecules, in particular concerning those aspect (e.g., kinetics, coexistence of different states and populations, transient interactions), which are typically hidden in ensemble measurements, such as those obtained with standard biochemical or microscopy methods. Thus, dynamic events, such as receptor-receptor interactions, can be followed in real time in a living cell with high spatiotemporal resolution. This protocol describes a method based on labeling with small and bright organic fluorophores and total internal reflection fluorescence (TIRF) microscopy to directly visualize single receptors on the surface of living cells. This approach allows one to precisely localize receptors, measure the size of receptor complexes, and capture dynamic events such as transient receptor-receptor interactions. The protocol provides a detailed description of how to perform a single-molecule experiment, including sample preparation, image acquisition and image analysis. As an example, the application of this method to analyze two G-protein-coupled receptors, i.e., &#946;2-adrenergic and &#947;-aminobutyric acid type B (GABAB) receptor, is reported. The protocol can be adapted to other membrane proteins and different cell models, transfection methods and labeling strategies.

This protocol describes how to use total internal reflection fluorescence microscopy to visualize and track single receptors on the surface of living cells and thereby analyze receptor lateral mobility, size of receptor complexes as well as to visualize transient receptor-receptor interactions. This protocol can be extended to other membrane proteins.

Single-molecule microscopy is emerging as a powerful approach to analyze the behavior of signaling molecules, in particular concerning those aspect (e.g., ...

Single Molecule Fluorescence Microscopy on Planar Supported Bilayers

In the course of a single decade single molecule microscopy has changed from being a secluded domain shared merely by physicists with a strong background in optics and laser physics to a discipline that is now enjoying vivid attention by life-scientists of all venues 1. This is because single molecule imaging has the unique potential to reveal protein behavior in situ in living cells and uncover cellular organization with unprecedented resolution below the diffraction limit of visible light 2. Glass-supported planar lipid bilayers (SLBs) are a powerful tool to bring cells otherwise growing in suspension in close enough proximity to the glass slide so that they can be readily imaged in noise-reduced Total Internal Reflection illumination mode 3,4. They are very useful to study the protein dynamics in plasma membrane-associated events as diverse as cell-cell contact formation, endocytosis, exocytosis and immune recognition. Simple procedures are presented how to generate highly mobile protein-functionalized SLBs in a reproducible manner, how to determine protein mobility within and how to measure protein densities with the use of single molecule detection. It is shown how to construct a cost-efficient single molecule microscopy system with TIRF illumination capabilities and how to operate it in the experiment.

Preparation of protein-functionalized planar glass-supported lipid bilayers, determination of protein mobility within and measurement of protein densities is shown here. A roadmap to building a noise-reduced Total Internal Reflection microscope is outlined, which allows visualizing single bilayer-resident fluorochromes with high spatiotemporal resolution.

In the course of a single decade single molecule microscopy has changed from being a secluded domain shared merely by physicists with a strong background ...

Label-free Single Molecule Detection Using Microtoroid Optical Resonators

Detecting small concentrations of molecules down to the single molecule limit has impact on areas such as early detection of disease, and fundamental studies on the behavior of molecules. Single molecule detection techniques commonly utilize labels such as fluorescent tags or quantum dots, however, labels are not always available, increase cost and complexity, and can perturb the events being studied. Optical resonators have emerged as a promising means to detect single molecules without the use of labels. Currently the smallest particle detected by a non-plasmonically-enhanced bare optical resonator system in solution is a 25 nm polystyrene sphere1. We have developed a technique known as Frequency Locking Optical Whispering Evanescent Resonator (FLOWER) that can surpass this limit and achieve label-free single molecule detection in aqueous solution2. As signal strength scales with particle volume, our work represents a &#62; 100x improvement in the signal to noise ratio (SNR) over the current state of the art. Here the procedures behind FLOWER are presented in an effort to increase its usage in the field.

We have developed a label-free biosensing system based on optical resonator technology known as Frequency Locking Optical Whispering Evanescent Resonator (FLOWER) that is capable of detecting single molecules in solution. Here the procedures behind this work are described and presented.

Detecting small concentrations of molecules down to the single molecule limit has impact on areas such as early detection of disease, and fundamental ...

Sensitive Detection of Proteopathic Seeding Activity with FRET Flow Cytometry

Increasing evidence supports transcellular propagation of toxic protein aggregates, or proteopathic seeds, as a mechanism for the initiation and progression of pathology in several neurodegenerative diseases, including Alzheimer's disease and the related tauopathies. The potentially critical role of tau seeds in disease progression strongly supports the need for a sensitive assay that readily detects seeding activity in biological samples. 
By combining the specificity of fluorescence resonance energy transfer (FRET), the sensitivity of flow cytometry, and the stability of a monoclonal cell line, an ultra-sensitive seeding assay has been engineered and is compatible with seed detection from recombinant or biological samples, including human and mouse brain homogenates. The assay employs monoclonal HEK 293T cells that stably express the aggregation-prone repeat domain (RD) of tau harboring the disease-associated P301S mutation fused to either CFP or YFP, which produce a FRET signal upon protein aggregation. The uptake of proteopathic tau seeds (but not other proteins) into the biosensor cells stimulates aggregation of RD-CFP and RD-YFP, and flow cytometry sensitively and quantitatively monitors this aggregation-induced FRET. The assay detects femtomolar concentrations (monomer equivalent) of recombinant tau seeds, has a dynamic range spanning three orders of magnitude, and is compatible with brain homogenates from tauopathy transgenic mice and human tauopathy subjects. With slight modifications, the assay can also detect seeding activity of other proteopathic seeds, such as &#945;-synuclein, and is also compatible with primary neuronal cultures. The ease, sensitivity, and broad applicability of FRET flow cytometry makes it useful to study a wide range of protein aggregation disorders.

Cell-to-cell transfer of protein aggregates, or proteopathic seeds, may underlie the progression of pathology in neurodegenerative diseases. Here, a novel FRET flow cytometry assay is described that enables specific and sensitive detection of seeding activity from recombinant or biological samples.

Increasing evidence supports transcellular propagation of toxic protein aggregates, or proteopathic seeds, as a mechanism for the initiation and ...

Fluorescence Recovery after Merging a Droplet to Measure the Two-dimensional Diffusion of a Phospholipid Monolayer

We introduce a new method to measure the lateral diffusivity of a surfactant monolayer at the fluid-fluid interface, called fluorescence recovery after merging (FRAM). FRAM adopts the same principles as the fluorescence recovery after photobleaching (FRAP) technique, especially for measuring fluorescence recovery after bleaching a specific area, but FRAM uses a drop coalescence instead of photobleaching dye molecules to induce a chemical potential gradient of dye molecules. Our technique has several advantages over FRAP: it only requires a fluorescence microscope rather than a confocal microscope equipped with high power lasers; it is essentially free from the selection of fluorescence dyes; and it has far more freedom to define the measured diffusion area. Furthermore, FRAM potentially provides a route for studying the mixing or inter-diffusion of two different surfactants, when the monolayers at a surface of droplet and at a flat air/water interface are prepared with different species, independently.

We present a new technique to measure the lateral diffusion of a surface active species at the fluid-fluid interface by merging a droplet monolayer onto a flat monolayer.

We introduce a new method to measure the lateral diffusivity of a surfactant monolayer at the fluid-fluid interface, called fluorescence recovery after ...

Automated Contraction Analysis of Human Engineered Heart Tissue for Cardiac Drug Safety Screening

Cardiac tissue engineering describes techniques to constitute three dimensional force-generating engineered tissues. For the implementation of these procedures in basic research and preclinical drug development, it is important to develop protocols for automated generation and analysis under standardized conditions. Here, we present a technique to generate engineered heart tissue (EHT) from cardiomyocytes of different species (rat, mouse, human). The technique relies on the assembly of a fibrin-gel containing dissociated cardiomyocytes between elastic polydimethylsiloxane (PDMS) posts in a 24-well format. Three-dimensional, force-generating EHTs constitute within two weeks after casting. This procedure allows for the generation of several hundred EHTs per week and is technically limited only by the availability of cardiomyocytes (0.4-1.0 x 106/EHT). Evaluation of auxotonic muscle contractions is performed in a modified incubation chamber with a mechanical interlock for 24-well plates and a camera placed on top of this chamber. A software controls a camera moved on an XYZ axis system to each EHT. EHT contractions are detected by an automated figure recognition algorithm, and force is calculated based on shortening of the EHT and the elastic propensity and geometry of the PDMS posts. This procedure allows for automated analysis of high numbers of EHT under standardized and sterile conditions. The reliable detection of drug effects on cardiomyocyte contraction is crucial for cardiac drug development and safety pharmacology. We demonstrate, with the example of the hERG channel inhibitor E-4031, that the human EHT system replicates drug responses on contraction kinetics of the human heart, indicating it to be a promising tool for cardiac drug safety screening.

Here, we show the generation of human engineered heart tissue from induced pluripotent stem cells (hiPSC)-derived cardiomyocytes. We present a method to analyze contraction force and exemplary alteration of contraction pattern by the hERG channel inhibitor E-4031. This method shows high level of robustness and suitability for cardiac drug screening.

Cardiac tissue engineering describes techniques to constitute three dimensional force-generating engineered tissues. For the implementation of these ...