TY - JOUR
T1 - Localization atomic force microscopy
AU - Heath, George R.
AU - Kots, Ekaterina
AU - Robertson, Janice L.
AU - Lansky, Shifra
AU - Khelashvili, George
AU - Weinstein, Harel
AU - Scheuring, Simon
N1 - Funding Information:
Acknowledgements This work was supported by grants from the National Institute of Health, NIH, DP1AT010874 (to S.S.) and R01GM120260 (to J.L.R.). We thank A. Razavi for help with the initial stages of the MD simulation analysis and for discussions. The computational work was performed using resources of the Oak Ridge Leadership Computing Facility (allocation BIP109 and Director’s Discretionary) at the Oak Ridge National Laboratory, which is a DOE Office of Science User Facility supported under contract DE-AC05-00OR22725; resources and support provided at the RPI Artificial Intelligence Multiprocessing Optimized System (AiMOS) system, accessed through an award from the COVID-19 HPC Consortium (https://covid19-hpc-consortium.org/); and the computational resources of the David A. Cofrin Center for Biomedical Information in Institute for Computational Biomedicine at Weill Cornell Medical College. Support from the 1923 Fund is gratefully acknowledged.
Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Nature Limited.
PY - 2021/6/17
Y1 - 2021/6/17
N2 - Understanding structural dynamics of biomolecules at the single-molecule level is vital to advancing our knowledge of molecular mechanisms. Currently, there are few techniques that can capture dynamics at the sub-nanometre scale and in physiologically relevant conditions. Atomic force microscopy (AFM)1 has the advantage of analysing unlabelled single molecules in physiological buffer and at ambient temperature and pressure, but its resolution limits the assessment of conformational details of biomolecules2. Here we present localization AFM (LAFM), a technique developed to overcome current resolution limitations. By applying localization image reconstruction algorithms3 to peak positions in high-speed AFM and conventional AFM data, we increase the resolution beyond the limits set by the tip radius, and resolve single amino acid residues on soft protein surfaces in native and dynamic conditions. LAFM enables the calculation of high-resolution maps from either images of many molecules or many images of a single molecule acquired over time, facilitating single-molecule structural analysis. LAFM is a post-acquisition image reconstruction method that can be applied to any biomolecular AFM dataset.
AB - Understanding structural dynamics of biomolecules at the single-molecule level is vital to advancing our knowledge of molecular mechanisms. Currently, there are few techniques that can capture dynamics at the sub-nanometre scale and in physiologically relevant conditions. Atomic force microscopy (AFM)1 has the advantage of analysing unlabelled single molecules in physiological buffer and at ambient temperature and pressure, but its resolution limits the assessment of conformational details of biomolecules2. Here we present localization AFM (LAFM), a technique developed to overcome current resolution limitations. By applying localization image reconstruction algorithms3 to peak positions in high-speed AFM and conventional AFM data, we increase the resolution beyond the limits set by the tip radius, and resolve single amino acid residues on soft protein surfaces in native and dynamic conditions. LAFM enables the calculation of high-resolution maps from either images of many molecules or many images of a single molecule acquired over time, facilitating single-molecule structural analysis. LAFM is a post-acquisition image reconstruction method that can be applied to any biomolecular AFM dataset.
UR - http://www.scopus.com/inward/record.url?scp=85108156558&partnerID=8YFLogxK
U2 - 10.1038/s41586-021-03551-x
DO - 10.1038/s41586-021-03551-x
M3 - Article
C2 - 34135520
AN - SCOPUS:85108156558
SN - 0028-0836
VL - 594
SP - 385
EP - 390
JO - Nature
JF - Nature
IS - 7863
ER -