Literature DB >> 35385658

High-Force Application by a Nanoscale DNA Force Spectrometer.

Michael Darcy, Kyle Crocker, Yuchen Wang, Jenny V Le, Golbarg Mohammadiroozbahani, Mahmoud A S Abdelhamid1, Timothy D Craggs1, Carlos E Castro, Ralf Bundschuh, Michael G Poirier.   

Abstract

The ability to apply and measure high forces (>10 pN) on the nanometer scale is critical to the development of nanomedicine, molecular robotics, and the understanding of biological processes such as chromatin condensation, membrane deformation, and viral packaging. Established force spectroscopy techniques including optical traps, magnetic tweezers, and atomic force microscopy rely on micron-sized or larger handles to apply forces, limiting their applications within constrained geometries including cellular environments and nanofluidic devices. A promising alternative to these approaches is DNA-based molecular calipers. However, this approach is currently limited to forces on the scale of a few piconewtons. To study the force application capabilities of DNA devices, we implemented DNA origami nanocalipers with tunable mechanical properties in a geometry that allows application of force to rupture a DNA duplex. We integrated static and dynamic single-molecule characterization methods and statistical mechanical modeling to quantify the device properties including force output and dynamic range. We found that the thermally driven dynamics of the device are capable of applying forces of at least 20 piconewtons with a nanometer-scale dynamic range. These characteristics could eventually be used to study other biomolecular processes such as protein unfolding or to control high-affinity interactions in nanomechanical devices or molecular robots.

Entities:  

Keywords:  DNA origami nanotechnology; DNA shearing; force spectroscopy; partition function modeling; single-molecule fluorescence

Year:  2022        PMID: 35385658      PMCID: PMC9048690          DOI: 10.1021/acsnano.1c10698

Source DB:  PubMed          Journal:  ACS Nano        ISSN: 1936-0851            Impact factor:   18.027


  62 in total

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Authors:  S Howorka; S Cheley; H Bayley
Journal:  Nat Biotechnol       Date:  2001-07       Impact factor: 54.908

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4.  Empirical Bayes methods enable advanced population-level analyses of single-molecule FRET experiments.

Authors:  Jan-Willem van de Meent; Jonathan E Bronson; Chris H Wiggins; Ruben L Gonzalez
Journal:  Biophys J       Date:  2014-03-18       Impact factor: 4.033

5.  Quantitative Modeling of Nucleosome Unwrapping from Both Ends.

Authors:  Dengke Zhao; Jenny V Le; Michael A Darcy; Kyle Crocker; Michael G Poirier; Carlos Castro; Ralf Bundschuh
Journal:  Biophys J       Date:  2019-10-30       Impact factor: 4.033

6.  Calcium-dependent folding of single calmodulin molecules.

Authors:  Johannes Stigler; Matthias Rief
Journal:  Proc Natl Acad Sci U S A       Date:  2012-07-02       Impact factor: 11.205

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Authors:  Colin Echeverría Aitken; R Andrew Marshall; Joseph D Puglisi
Journal:  Biophys J       Date:  2007-10-05       Impact factor: 4.033

8.  Predicting stability of DNA duplexes in solutions containing magnesium and monovalent cations.

Authors:  Richard Owczarzy; Bernardo G Moreira; Yong You; Mark A Behlke; Joseph A Walder
Journal:  Biochemistry       Date:  2008-04-19       Impact factor: 3.162

9.  DNA origami-based single-molecule force spectroscopy elucidates RNA Polymerase III pre-initiation complex stability.

Authors:  Kevin Kramm; Tim Schröder; Jerome Gouge; Andrés Manuel Vera; Kapil Gupta; Florian B Heiss; Tim Liedl; Christoph Engel; Imre Berger; Alessandro Vannini; Philip Tinnefeld; Dina Grohmann
Journal:  Nat Commun       Date:  2020-06-05       Impact factor: 14.919

Review 10.  SciPy 1.0: fundamental algorithms for scientific computing in Python.

Authors:  Pauli Virtanen; Ralf Gommers; Travis E Oliphant; Matt Haberland; Tyler Reddy; David Cournapeau; Evgeni Burovski; Pearu Peterson; Warren Weckesser; Jonathan Bright; Stéfan J van der Walt; Matthew Brett; Joshua Wilson; K Jarrod Millman; Nikolay Mayorov; Andrew R J Nelson; Eric Jones; Robert Kern; Eric Larson; C J Carey; İlhan Polat; Yu Feng; Eric W Moore; Jake VanderPlas; Denis Laxalde; Josef Perktold; Robert Cimrman; Ian Henriksen; E A Quintero; Charles R Harris; Anne M Archibald; Antônio H Ribeiro; Fabian Pedregosa; Paul van Mulbregt
Journal:  Nat Methods       Date:  2020-02-03       Impact factor: 28.547

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