Localization atomic force microscopy
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 (AF...
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Published in | Nature (London) Vol. 594; no. 7863; pp. 385 - 390 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
17.06.2021
Nature Publishing Group |
Subjects | |
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Abstract | 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 biomolecules
2
. Here we present localization AFM (LAFM), a technique developed to overcome current resolution limitations. By applying localization image reconstruction algorithms
3
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.
A localization algorithm is applied to datasets obtained with conventional and high-speed atomic force microscopy to increase image resolution beyond the limits set by the radius of the tip used. |
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AbstractList | 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).sup.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 biomolecules.sup.2. Here we present localization AFM (LAFM), a technique developed to overcome current resolution limitations. By applying localization image reconstruction algorithms.sup.3 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. 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. 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 biomolecules 2 . Here we present localization AFM (LAFM), a technique developed to overcome current resolution limitations. By applying localization image reconstruction algorithms 3 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. A localization algorithm is applied to datasets obtained with conventional and high-speed atomic force microscopy to increase image resolution beyond the limits set by the radius of the tip used. 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).sup.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 biomolecules.sup.2. Here we present localization AFM (LAFM), a technique developed to overcome current resolution limitations. By applying localization image reconstruction algorithms.sup.3 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. A localization algorithm is applied to datasets obtained with conventional and high-speed atomic force microscopy to increase image resolution beyond the limits set by the radius of the tip used. 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-nanometer scale and in physiologically relevant conditions. Atomic force microscopy (AFM 1 ) has the notable advantage of analyzing unlabeled single molecules in physiological buffer and at ambient temperature and pressure, yet its resolution has been limiting to assess conformational details of biomolecules. 2 To move beyond current resolution limitations, we developed Localization AFM (LAFM). By applying localization image reconstruction algorithms 3 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. The LAFM method allows the calculation of high-resolution maps from either images of many molecules or many images of a single molecule acquired over time, opening new avenues for single molecule structural analysis. LAFM is a post-acquisition image reconstruction method that can be applied to any biomolecular AFM dataset. 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) 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 biomolecules . Here we present localization AFM (LAFM), a technique developed to overcome current resolution limitations. By applying localization image reconstruction algorithms 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. |
Audience | Academic |
Author | Kots, Ekaterina Weinstein, Harel Scheuring, Simon Robertson, Janice L. Khelashvili, George Lansky, Shifra Heath, George R. |
AuthorAffiliation | 3 Washington University, Department of Biochemistry and Molecular Biophysics, 660 South Euclid Avenue, St. Louis, MO-63110, USA 2 Weill Cornell Medicine, Department of Physiology and Biophysics, 1300 York Avenue, New York, NY-10065, USA 1 Weill Cornell Medicine, Department of Anesthesiology, 1300 York Avenue, New York, NY-10065, USA |
AuthorAffiliation_xml | – name: 1 Weill Cornell Medicine, Department of Anesthesiology, 1300 York Avenue, New York, NY-10065, USA – name: 3 Washington University, Department of Biochemistry and Molecular Biophysics, 660 South Euclid Avenue, St. Louis, MO-63110, USA – name: 2 Weill Cornell Medicine, Department of Physiology and Biophysics, 1300 York Avenue, New York, NY-10065, USA |
Author_xml | – sequence: 1 givenname: George R. orcidid: 0000-0001-6431-2191 surname: Heath fullname: Heath, George R. organization: Department of Anesthesiology, Weill Cornell Medicine, School of Physics and Astronomy, University of Leeds – sequence: 2 givenname: Ekaterina orcidid: 0000-0002-7139-7098 surname: Kots fullname: Kots, Ekaterina organization: Department of Physiology and Biophysics, Weill Cornell Medicine – sequence: 3 givenname: Janice L. orcidid: 0000-0002-5499-9943 surname: Robertson fullname: Robertson, Janice L. organization: Department of Biochemistry and Molecular Biophysics, Washington University – sequence: 4 givenname: Shifra surname: Lansky fullname: Lansky, Shifra organization: Department of Anesthesiology, Weill Cornell Medicine – sequence: 5 givenname: George orcidid: 0000-0001-7235-8579 surname: Khelashvili fullname: Khelashvili, George organization: Department of Physiology and Biophysics, Weill Cornell Medicine – sequence: 6 givenname: Harel orcidid: 0000-0003-3473-9818 surname: Weinstein fullname: Weinstein, Harel organization: Department of Physiology and Biophysics, Weill Cornell Medicine – sequence: 7 givenname: Simon orcidid: 0000-0003-3534-069X surname: Scheuring fullname: Scheuring, Simon email: sis2019@med.cornell.edu organization: Department of Anesthesiology, Weill Cornell Medicine, Department of Physiology and Biophysics, Weill Cornell Medicine |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/34135520$$D View this record in MEDLINE/PubMed |
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Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Detailed Author Contribution Statement G.R.H. and S.S. designed the study and developed the LAFM algorithm; J.L.R purified and reconstituted the CLC-ec1. G.R.H. and S.L. performed HS-AFM experiments. E.K. and G.K. performed CLC MD simulations. S.L. performed A5 P13W-G14W cloning, expression, purification and MD simulations. G.R.H., E.K., G.K., H.W. and S.S. analyzed the data. G.R.H., E.K., J.L.R, G.K., H.W. and S.S. wrote the paper. Current address: School of Physics and Astronomy, University of Leeds, Leeds, LS2 9JT, UK. |
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