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Label-free, atomic force microscopy-based mapping of DNA intrinsic curvature for the nanoscale comparative analysis of bent duplexes.

Buzio R, Repetto L, Giacopelli F, Ravazzolo R, Valbusa U - Nucleic Acids Res. (2012)

Bottom Line: We demonstrate by theoretical arguments and experimental investigation of representative samples that the fine mapping of the average product along the molecular backbone generates a characteristic pattern of variation that effectively highlights all pairs of DNA tracts with large intrinsic curvature.Notably, such an assay is virtually inaccessible to the automated intrinsic curvature computation algorithms proposed so far.We foresee several challenging applications, including the validation of DNA adsorption and bending models by experiments and the discrimination of specimens for genetic screening purposes.

View Article: PubMed Central - PubMed

Affiliation: S.C. Nanobiotecnologie, National Institute for Cancer Research IST, Genova, Italy.

ABSTRACT
We propose a method for the characterization of the local intrinsic curvature of adsorbed DNA molecules. It relies on a novel statistical chain descriptor, namely the ensemble averaged product of curvatures for two nanosized segments, symmetrically placed on the contour of atomic force microscopy imaged chains. We demonstrate by theoretical arguments and experimental investigation of representative samples that the fine mapping of the average product along the molecular backbone generates a characteristic pattern of variation that effectively highlights all pairs of DNA tracts with large intrinsic curvature. The centrosymmetric character of the chain descriptor enables targetting strands with unknown orientation. This overcomes a remarkable limitation of the current experimental strategies that estimate curvature maps solely from the trajectories of end-labeled molecules or palindromes. As a consequence our approach paves the way for a reliable, unbiased, label-free comparative analysis of bent duplexes, aimed to detect local conformational changes of physical or biological relevance in large sample numbers. Notably, such an assay is virtually inaccessible to the automated intrinsic curvature computation algorithms proposed so far. We foresee several challenging applications, including the validation of DNA adsorption and bending models by experiments and the discrimination of specimens for genetic screening purposes.

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(a) The intrinsic curvature profile estimated by the FF algorithm is compared with the corresponding curve predicted by the theoretical approach described in previous subsection. (b) The CP pattern computed from the intrinsic curvature profile in (a) is compared with the CP profile directly estimated on experimental DNA trajectories by our protocol.
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gks210-F7: (a) The intrinsic curvature profile estimated by the FF algorithm is compared with the corresponding curve predicted by the theoretical approach described in previous subsection. (b) The CP pattern computed from the intrinsic curvature profile in (a) is compared with the CP profile directly estimated on experimental DNA trajectories by our protocol.

Mentions: The intrinsic curvature profile of the human OPN coding gene was reconstructed by applying the FF algorithm to an ensemble of 100 molecular profiles extracted from AFM images. Figure 7a contrasts the reconstructed profile with De Santis et al. model predictions. The two profiles show very comparable features, in particular two regions of large curvature at and , respectively, (peaks 2 and 5) and a well-defined sequence of smaller local peaks at similar curvilinear positions (peaks 8–12).Figure 7.


Label-free, atomic force microscopy-based mapping of DNA intrinsic curvature for the nanoscale comparative analysis of bent duplexes.

Buzio R, Repetto L, Giacopelli F, Ravazzolo R, Valbusa U - Nucleic Acids Res. (2012)

(a) The intrinsic curvature profile estimated by the FF algorithm is compared with the corresponding curve predicted by the theoretical approach described in previous subsection. (b) The CP pattern computed from the intrinsic curvature profile in (a) is compared with the CP profile directly estimated on experimental DNA trajectories by our protocol.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3367213&req=5

gks210-F7: (a) The intrinsic curvature profile estimated by the FF algorithm is compared with the corresponding curve predicted by the theoretical approach described in previous subsection. (b) The CP pattern computed from the intrinsic curvature profile in (a) is compared with the CP profile directly estimated on experimental DNA trajectories by our protocol.
Mentions: The intrinsic curvature profile of the human OPN coding gene was reconstructed by applying the FF algorithm to an ensemble of 100 molecular profiles extracted from AFM images. Figure 7a contrasts the reconstructed profile with De Santis et al. model predictions. The two profiles show very comparable features, in particular two regions of large curvature at and , respectively, (peaks 2 and 5) and a well-defined sequence of smaller local peaks at similar curvilinear positions (peaks 8–12).Figure 7.

Bottom Line: We demonstrate by theoretical arguments and experimental investigation of representative samples that the fine mapping of the average product along the molecular backbone generates a characteristic pattern of variation that effectively highlights all pairs of DNA tracts with large intrinsic curvature.Notably, such an assay is virtually inaccessible to the automated intrinsic curvature computation algorithms proposed so far.We foresee several challenging applications, including the validation of DNA adsorption and bending models by experiments and the discrimination of specimens for genetic screening purposes.

View Article: PubMed Central - PubMed

Affiliation: S.C. Nanobiotecnologie, National Institute for Cancer Research IST, Genova, Italy.

ABSTRACT
We propose a method for the characterization of the local intrinsic curvature of adsorbed DNA molecules. It relies on a novel statistical chain descriptor, namely the ensemble averaged product of curvatures for two nanosized segments, symmetrically placed on the contour of atomic force microscopy imaged chains. We demonstrate by theoretical arguments and experimental investigation of representative samples that the fine mapping of the average product along the molecular backbone generates a characteristic pattern of variation that effectively highlights all pairs of DNA tracts with large intrinsic curvature. The centrosymmetric character of the chain descriptor enables targetting strands with unknown orientation. This overcomes a remarkable limitation of the current experimental strategies that estimate curvature maps solely from the trajectories of end-labeled molecules or palindromes. As a consequence our approach paves the way for a reliable, unbiased, label-free comparative analysis of bent duplexes, aimed to detect local conformational changes of physical or biological relevance in large sample numbers. Notably, such an assay is virtually inaccessible to the automated intrinsic curvature computation algorithms proposed so far. We foresee several challenging applications, including the validation of DNA adsorption and bending models by experiments and the discrimination of specimens for genetic screening purposes.

Show MeSH