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Automation of peak-tracking analysis of stepwise perturbed NMR spectra

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Abstract

We describe a new algorithmic approach able to automatically pick and track the NMR resonances of a large number of 2D NMR spectra acquired during a stepwise variation of a physical parameter. The method has been named Trace in Track (TinT), referring to the idea that a gaussian decomposition traces peaks within the tracks recognised through 3D mathematical morphology. It is capable of determining the evolution of the chemical shifts, intensity and linewidths of each tracked peak.The performances obtained in term of track reconstruction and correct assignment on realistic synthetic spectra were high above 90% when a noise level similar to that of experimental data were considered. TinT was applied successfully to several protein systems during a temperature ramp in isotope exchange experiments. A comparison with a state-of-the-art algorithm showed promising results for great numbers of spectra and low signal to noise ratios, when the graduality of the perturbation is appropriate. TinT can be applied to different kinds of high throughput chemical shift mapping experiments, with quasi-continuous variations, in which a quantitative automated recognition is crucial.

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Acknowledgements

TB would like to thank Richard Jang for providing PeakWalker and assisting in using it. The work received financial support from PRIN Project No. 2012A7LMS3. TB was supported by the Social European Fund and sponsored by Bruker.

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Authors and Affiliations

  1. Dipartimento di Area Medica, Università di Udine, P.le Kolbe, 4, 33100, Udine, Italy

    Tommaso Banelli, Marco Vuano & Alessandra Corazza

  2. INBB, Viale Medaglie d’Oro, 306, 00136, Roma, Italy

    Federico Fogolari, Gennaro Esposito & Alessandra Corazza

  3. Dipartimento di Scienze Matematiche Informatiche e Fisiche, Università di Udine, Via delle Scienze, 206, 33100, Udine, Italy

    Federico Fogolari & Gennaro Esposito

  4. Dipartimento Politecnico di Ingegneria e Architettura, Università di Udine, Via delle Scienze, 208, 33100, Udine, Italy

    Andrea Fusiello

  5. Science & Math Division, New York University Abu Dhabi, Saadiyat Campus, PO Box 129188, Abu Dhabi, UAE

    Gennaro Esposito

Authors
  1. Tommaso Banelli
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  2. Marco Vuano
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  3. Federico Fogolari
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  4. Andrea Fusiello
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  5. Gennaro Esposito
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  6. Alessandra Corazza
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Correspondence to Alessandra Corazza.

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Banelli, T., Vuano, M., Fogolari, F. et al. Automation of peak-tracking analysis of stepwise perturbed NMR spectra. J Biomol NMR 67, 121–134 (2017). https://doi.org/10.1007/s10858-017-0088-7

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  • DOI: https://doi.org/10.1007/s10858-017-0088-7

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