By exploiting a phenomenon known as Förster resonance energy transfer (FRET), it is possible to monitor the motions of single molecules in living cells in real time. The data provided by single-molecule FRET therefore yield important insights into the structural dynamics of the molecular machinery which is the basis of life. A worldwide study involving 20 laboratories has now succeeded in enhancing the utility and precision of the method significantly. Three groups at LMU, led by Prof. Thorben Cordes, Prof. Don C. Lamb, and Prof. Philip Tinnefeld, contributed to the study, which was recently published in Nature Methods.
FRET works rather like proximity sensors in cars. The closer the object is to the sensor, the louder or more frequent the signals become. Instead of relying on acoustics, FRET is based on proximity-dependent changes in the fluorescence emitted by two dyes, which are detected by sensitive microscopes. The technology has revolutionized the analysis of the motions and interactions of biomolecules in living cells.
So far, the technology has mainly been used to report changes in relative distances – for instance, whether the molecules have moved closer together or farther apart. However, the accuracy and reproducibility of the results have always been questioned. In the new study, researchers in 20 laboratories have developed a standardized procedure which has refined the precision of the method and greatly improved its reproducibility. Absolute distances between molecules can now be measured accurately even in the sub-nanometer range (equivalent to one millionth of the width of a human hair) in different laboratories, irrespective of the particular microscope or analysis software employed. According to the authors, the absolute distance information that can be acquired with this method will enable accurate assignment of conformations to dynamic biomolecules, and may even permit full-scale structure determinations. The research consortium was led by groups based at the universities of Freiburg, Düsseldorf, Ulm and Sheffield (UK).
Nature Methods 2018