Abstract
Implementation of a new algorithm, SMILE, is described for reconstruction of non-uniformly sampled two-, three- and four-dimensional NMR data, which takes advantage of the known phases of the NMR spectrum and the exponential decay of underlying time domain signals. The method is very robust with respect to the chosen sampling protocol and, in its default mode, also extends the truncated time domain signals by a modest amount of non-sampled zeros. SMILE can likewise be used to extend conventional uniformly sampled data, as an effective multidimensional alternative to linear prediction. The program is provided as a plug-in to the widely used NMRPipe software suite, and can be used with default parameters for mainstream application, or with user control over the iterative process to possibly further improve reconstruction quality and to lower the demand on computational resources. For large data sets, the method is robust and demonstrated for sparsities down to ca 1%, and final all-real spectral sizes as large as 300 Gb. Comparison between fully sampled, conventionally processed spectra and randomly selected NUS subsets of this data shows that the reconstruction quality approaches the theoretical limit in terms of peak position fidelity and intensity. SMILE essentially removes the noise-like appearance associated with the point-spread function of signals that are a default of five-fold above the noise level, but impacts the actual thermal noise in the NMR spectra only minimally. Therefore, the appearance and interpretation of SMILE-reconstructed spectra is very similar to that of fully sampled spectra generated by Fourier transformation.
Similar content being viewed by others
References
Balsgart NM, Vosegaard T (2012) Fast forward maximum entropy reconstruction of sparsely sampled data. J Magn Reson 223:164–169
Barna JCJ, Laue ED, Mayger MR, Skilling J, Worrall SJP (1987) Exponential sampling, an alternative method for sampling in two-dimensional NMR experiments. J Magn Reson 73:69–77
Bax A, Pochapsky SS (1992) Optimized recording of heteronuclear multidimensional NMR-spectra using pulsed field gradients. J Magn Reson 99:638–643
Bermel W, Felli IC, Gonnelli L, Kozminski W, Piai A, Pierattelli R, Zawadzka-Kazimierczuk A (2013) High-dimensionality C-13 direct-detected NMR experiments for the automatic assignment of intrinsically disordered proteins. J Biomol NMR 57:353–361
Bostock MJ, Holland DJ, Nietlispach D (2012) Compressed sensing reconstruction of undersampled 3D NOESY spectra: application to large membrane proteins. J Biomol NMR 54:15–32
Clore GM, Kay LE, Bax A, Gronenborn AM (1991) 4-Dimensional C-13/C-13-edited nuclear overhauser enhancement spectroscopy of a protein in solution—application to interleukin 1-Beta. Biochemistry 30:12–18
Coggins BE, Zhou P (2008) High resolution 4-D spectroscopy with sparse concentric shell sampling and FFT-CLEAN. J Biomol NMR 42:225–239
Coggins BE, Venters RA, Zhou P (2010) Radial sampling for fast NMR: concepts and practices over three decades. Prog Nucl Magn Reson Spectrosc 57:381–419
Coggins BE, Werner-Allen JW, Yan A, Zhou P (2012) Rapid protein global fold determination using ultrasparse sampling, high-dynamic range artifact suppression, and time-shared NOESY. J Am Chem Soc 134:18619–18630
Delaglio F, Grzesiek S, Vuister GW, Zhu G, Pfeifer J, Bax A (1995) NMRpipe—a multidimensional spectral processing system based on UNIX pipes. J Biomol NMR 6:277–293
Delsuc MA, Tramesel D (2006) Application of maximum-entropy processing to NMR multidimensional datasets, partial sampling case. C R Chim 9:364–373
Eghbalnia HR, Bahrami A, Tonelli M, Hallenga K, Markley JL (2005) High-resolution iterative frequency identification for NMR as a general strategy for multidimensional data collection. J Am Chem Soc 127:12528–12536
Fiorito F, Hiller S, Wider G, Wuthrich K (2006) Automated resonance assignment of proteins: 6D APSY-NMR. J Biomol NMR 35:27–37
Hiller S, Ibraghimov I, Wagner G, Orekhov VY (2009) Coupled decomposition of four-dimensional NOESY spectra. J Am Chem Soc 131:12970–12978
Hoch JC, Maciejewski MW, Mobli M, Schuyler AD, Stern AS (2014) Nonuniform sampling and maximum entropy reconstruction in multidimensional NMR. Acc Chem Res 47:708–717
Holland DJ, Bostock MJ, Gladden LF, Nietlispach D (2011) Fast multidimensional NMR spectroscopy using compressed sensing. Angew Chem Int Ed 50:6548–6551
Hu JS, Bax A (1996) Measurement of three-bond C–13–C–13 J couplings between carbonyl and carbonyl/carboxyl carbons in isotopically enriched proteins. J Am Chem Soc 118:8170–8171
Hyberts SG, Takeuchi K, Wagner G (2010) Poisson-gap sampling and forward maximum entropy reconstruction for enhancing the resolution and sensitivity of protein NMR data. J Am Chem Soc 132:2145–2147
Hyberts SG, Milbradt AG, Wagner AB, Arthanari H, Wagner G (2012) Application of iterative soft thresholding for fast reconstruction of NMR data non-uniformly sampled with multidimensional Poisson Gap scheduling. J Biomol NMR 52:315–327
Hyberts SG, Robson SA, Wagner G (2013) Exploring signal-to-noise ratio and sensitivity in non-uniformly sampled multi-dimensional NMR spectra. J Biomol NMR 55:167–178
Kay LE, Clore GM, Bax A, Gronenborn AM (1990) Four-dimensional heteronuclear triple-resonance NMR spectroscopy of interleukin-1B in solution. Science 249:411–414
Kazimierczuk K, Orekhov VY (2011) Accelerated NMR spectroscopy by using compressed sensing. Angew Chem Int Ed 50:5556–5559
Kazimierczuk K, Stanek J, Zawadzka-Kazimierczuk A, Kozminski W (2010) Random sampling in multidimensional NMR spectroscopy. Prog Nucl Magn Reson Spectrosc 57:420–434
Kim S, Szyperski T (2003) GFT NMR, a new approach to rapidly obtain precise high-dimensional NMR spectral information. J Am Chem Soc 125:1385–1393
Kontaxis G, Clore GM, Bax A (2000) Evaluation of cross-correlation effects and measurement of one-bond couplings in proteins with short transverse relaxation times. J Magn Reson 143:184–196
Krishnamurthy K (2013) CRAFT (complete reduction to amplitude frequency table)—robust and time-efficient Bayesian approach for quantitative mixture analysis by NMR. Magn Reson Chem 51:821–829
Led JJ, Gesmar H (1991) Application of the linear prediction method to NMR spectroscopy. Chem Rev 91:1413–1426
Lee JH, Li F, Grishaev A, Bax A (2015) Quantitative residue-specific protein backbone torsion angle dynamics from concerted measurement of 3 J couplings. J Am Chem Soc 137:1432–1435
Levitt MH, Bodenhausen G, Ernst RR (1984) Sensitivity of two-dimensional spectra. J Magn Reson 58:462–472
Li F, Lee JH, Grishaev A, Ying J, Bax A (2015) High accuracy of karplus equations for relating three-bond J couplings to protein backbone torsion angles. ChemPhysChem 16:572–578
Linser R, Gelev V, Hagn F, Arthanari H, Hyberts SG, Wagner G (2014) Selective methyl labeling of eukaryotic membrane proteins using cell-free expression. J Am Chem Soc 136:11308–11310
Mayzel M, Kazimierczuk K, Orekhov VY (2014) The causality principle in the reconstruction of sparse NMR spectra. Chem Commun 50:8947–8950
Mobli M, Hoch JC (2014) Nonuniform sampling and non-Fourier signal processing methods in multidimensional NMR. Prog Nucl Magn Reson Spectrosc 83:21–41
Mobli M, Maciejewski MW, Gryk MR, Hoch JC (2007) Automatic maximum entropy spectral reconstruction in NMR. J Biomol NMR 39:133–139
Nowakowski M, Saxena S, Stanek J, Zerko S, Kozminski W (2015) Applications of high dimensionality experiments to biomolecular NMR. Prog Nucl Magn Reson Spectrosc 90–91:49–73
OpenMP Architecture Review Board, OpenMP Application Program Interface, Version 3.1, July 2011, http://www.openmp.org
Orekhov VY, Jaravine VA (2011) Analysis of non-uniformly sampled spectra with multi-dimensional decomposition. Prog Nucl Magn Reson Spectrosc 59:271–292
Orekhov VY, Ibraghimov I, Billeter M (2003) Optimizing resolution in multidimensional NMR by three-way decomposition. J Biomol NMR 27:165–173
Otting G, Widmer H, Wagner G, Wüthrich K (1986) Origin of t 1 and t 2 ridges in 2D NMR spectra and procedures for suppresion. J Magn Reson 66:187–193
Piai A, Hosek T, Gonnelli L, Zawadzka-Kazimierczuk A, Kozminski W, Brutscher B, Bermel W, Pierattelli R, Felli IC (2014) “CON–CON’’ assignment strategy for highly flexible intrinsically disordered proteins. J Biomol NMR 60:209–218
Rovnyak D, Frueh DP, Sastry M, Sun ZYJ, Stern AS, Hoch JC, Wagner G (2004) Accelerated acquisition of high resolution triple-resonance spectra using non-uniform sampling and maximum entropy reconstruction. J Magn Reson 170:15–21
Sgourakis NG, Natarajan K, Ying J, Vogeli B, Boyd LF, Margulies DH, Bax A (2014) The structure of mouse cytomegalovirus m04 protein obtained from sparse NMR data reveals a conserved fold of the m02–m06 viral immune modulator family. Structure 22:1263–1273
Sheppard D, Guo CY, Tugarinov V (2009) 4D H-1-C-13 NMR spectroscopy for assignments of alanine methyls in large and complex protein structures. J Am Chem Soc 131:1364–1365
Stanek J, Kozminski W (2010) Iterative algorithm of discrete Fourier transform for processing randomly sampled NMR data sets. J Biomol NMR 47:65–77
Stanek J, Augustyniak R, Kozminski W (2012) Suppression of sampling artefacts in high-resolution four-dimensional NMR spectra using signal separation algorithm. J Magn Reson 214:91–102
Stern AS, Hoch JC (2015) A new approach to compressed sensing for NMR. Magn Reson Chem 53:908–912
Stern AS, Li KB, Hoch JC (2002) Modern spectrum analysis in multidimensional NMR spectroscopy: comparison of linear-prediction extrapolation and maximum-entropy reconstruction. J Am Chem Soc 124:1982–1993
Stern AS, Donoho DL, Hoch JC (2007) NMR data processing using iterative thresholding and minimum l(1)-norm reconstruction. J Magn Reson 188:295–300
Sun SJ, Gill M, Li YF, Huang M, Byrd RA (2015) Efficient and generalized processing of multidimensional NUS NMR data: the NESTA algorithm and comparison of regularization terms. J Biomol NMR 62:105–117
Tjandra N, Grzesiek S, Bax A (1996) Magnetic field dependence of nitrogen-proton J splittings in N- 15-enriched human ubiquitin resulting from relaxation interference and residual dipolar coupling. J Am Chem Soc 118:6264–6272
Tugarinov V, Kay LE, Ibraghimov I, Orekhov VY (2005) High-resolution four-dimensional H-1-C-13 NOE spectroscopy using methyl-TROSY, sparse data acquisition, and multidimensional decomposition. J Am Chem Soc 127:2767–2775
Undheim EAB, Grimm LL, Low CF, Morgenstern D, Herzig V, Zobel-Thropp P, Pineda SS, Habib R, Dziemborowicz S, Fry BG, Nicholson GM, Binford GJ, Mobli M, King GF (2015) Weaponization of a hormone: convergent recruitment of hyperglycemic hormone into the venom of arthropod predators. Structure 23:1283–1292
Werner-Allen JW, Coggins BE, Zhou P (2010) Fast acquisition of high resolution 4-D amide–amide NOESY with diagonal suppression, sparse sampling and FFT-CLEAN. J Magn Reson 204:173–178
Xiao Y, Warner LR, Latham MP, Ahn NG, Pardi A (2015) Structure-based assignment of ile, leu, and val methyl groups in the active and inactive forms of the mitogen-activated protein kinase extracellular signal-regulated kinase. Biochemistry 54:4307–4319
Ying JF, Chill JH, Louis JM, Bax A (2007) Mixed-time parallel evolution in multiple quantum NMR experiments: sensitivity and resolution enhancement in heteronuclear NMR. J Biomol NMR 37:195–204
Yoon JW, Godsill S, Kupce E, Freeman R (2006) Deterministic and statistical methods for reconstructing multidimensional NMR spectra. Magn Reson Chem 44:197–209
Zhu G, Bax A (1990) Improved linear prediction for truncated signals of known phase. J Magn Reson 90:405–410
Zhu G, Torchia DA, Bax A (1993) Discrete Fourier transformation of NMR signals. The relationship between sampling delay time and spectral baseline. J Magn Reson Ser A 105:219–222
Zuiderweg ERP, Petros AM, Fesik SW, Olejniczak ET (1991) 4-Dimensional [C-13, H-1, C-13, H-1] HMQC-NOE-HMQC NMR spectroscopy—resolving tertiary NOE distance constraints in the spectra of larger proteins. J Am Chem Soc 113:370–372
Acknowledgements
We thank Alex Maltsev and Yang Shen for useful discussions, James L Baber and Dan Garrett for technical assistance, and Jung Ho Lee, Venkatraman Ramanujam, and Nikolaos Sgourakis for providing experimental data sets used for testing and illustrating the performance of SMILE. We also thank Michal Górka, Szymon Żerko, and Wiktor Koźmiński for providing the reconstructed (H)N(COCO)NH data by SSA, Victor Jaravine and Vladislav Orekhov for their help with running the MddNMR program, and Brian Coggins for helpful discussions about using SCRUB. This work was supported by the Intramural Research Program of the NIDDK and by the Intramural Antiviral Target Program of the Office of the Director, NIH. We acknowledge use of the high-performance computational capabilities of the NIH Biowulf Linux cluster. Funding was provided by National Institute of Diabetes and Digestive and Kidney Diseases (Grant No. ZIA DK029046-10).
Author information
Authors and Affiliations
Corresponding authors
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Ying, J., Delaglio, F., Torchia, D.A. et al. Sparse multidimensional iterative lineshape-enhanced (SMILE) reconstruction of both non-uniformly sampled and conventional NMR data. J Biomol NMR 68, 101–118 (2017). https://doi.org/10.1007/s10858-016-0072-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10858-016-0072-7