Atomic force microscopy (AFM) is a technique widely used to image or apply forces to surface- bound biomolecules in liquid. Traditional methods for imaging DNA and protein-DNA complexes in liquid have drawbacks: DNA conformations with an anomalous persistence length, low SNR, and/or ionic conditions detrimental to preserving native protein-DNA interactions. Here, we introduce a minimally perturbative method for imaging surface-bound DNA that improves data quality and quantity. In comparison to prior protocols, an eight-fold larger fraction (90%) of 680-nm-long DNA molecules were quantifiable, and the technique is viable for imaging DNA of many lengths and proteins in a variety of physiological buffers. In addition to improving AFM imaging, this work also advances the reliability and accuracy of single-molecule force spectroscopy (SMFS) AFM experiments. In particular, recent improvements in time resolution and data throughput of SMFS experiments highlight the need for high-precision, automated characterization of force-induced intra- and inter-molecular bond ruptures. Here, we introduce a new algorithm to automatically identify the locations of molecular ruptures in SMFS data. In order to improve molecular energy landscape characterization, we also applied the inverse Weierstrass transform to SMFS data and removed the energy associated with the AFM force probe, yielding the molecular free-energy landscape. Combined, these improvements in AFM methodology – minimally perturbative imaging of DNA-protein complexes, automated detection of molecular rupture events, and energy deconvolution of force probes – advance the quality and reproducibility of biophysical insights gained from AFM- based experiments.
Patrick Heenan / JILA, Perkins group
Event Details & Abstracts