High fidelity sampling schedules for NMR spectra of high dynamic range.

The ability to reconstruct non-uniformly sampled (NUS) NMR spectra has mostly been accepted. Still a concern is lingering regarding artifacts from sampling non-uniformly. As experienced, some sampling schedules yield better results than others. Finding a useful schedule is relatively trivial for a low dynamic range spectrum and a conservative sparsity, but not so when the dynamic range is large and/or when extreme sparsity is used. High dynamic range is typically found in NOESY and spectra of metabolites, where quantification of peak heights is desired at high fidelity. Extreme sparsity is desired when high throughput is a goal. In all cases, selecting a poor sampling schedule can create unnecessary artifacts. Effectively, it is important to select a sampling schedule that provides a signal-to-artifact apex ratio (SAAR) value in par or better than the signal-to-noise ratio (SNR) value. Notably, by signal-to-artifact apex ratio we consider reconstruction fidelity as the apex intensity likeness, i.e., as the true signal to the tallest artifact. We show that the quality of reconstruction depends on the particular sampling schedule. We evaluate the reconstruction quality in the frequency domain following a matched Lorentz-to-Gauss transform plus common apodization and Fourier Transform. As the Lorentz-to-Gauss transform improves resolution and reduces ridges we include this when defining the Signal-to-Artifact Apex Ratio (SAAR) metric. This metric measures the ratio of simulated reconstructed peak height to the tallest artifact of reconstruction in a spectrum without noise. Once a NUS schedule is found with an optimal SAAR it will be satisfactory for all spectra recorded with the same parameter set. Tables with good seed values are provided in the supplement.

NUScon: a community-driven platform for quantitative evaluation of nonuniform sampling in NMR.

Although the concepts of nonuniform sampling (NUS​​​​​​​) and non-Fourier spectral reconstruction in multidimensional NMR began to emerge 4 decades ago , it is only relatively recently that NUS has become more commonplace. Advantages of NUS include the ability to tailor experiments to reduce data collection time and to improve spectral quality, whether through detection of closely spaced peaks (i.e., "resolution") or peaks of weak intensity (i.e., "sensitivity"). Wider adoption of these methods is the result of improvements in computational performance, a growing abundance and flexibility of software, support from NMR spectrometer vendors, and the increased data sampling demands imposed by higher magnetic fields. However, the identification of best practices still remains a significant and unmet challenge. Unlike the discrete Fourier transform, non-Fourier methods used to reconstruct spectra from NUS data are nonlinear, depend on the complexity and nature of the signals, and lack quantitative or formal theory describing their performance. Seemingly subtle algorithmic differences may lead to significant variabilities in spectral qualities and artifacts. A community-based critical assessment of NUS challenge problems has been initiated, called the "Nonuniform Sampling Contest" (NUScon), with the objective of determining best practices for processing and analyzing NUS experiments. We address this objective by constructing challenges from NMR experiments that we inject with synthetic signals, and we process these challenges using workflows submitted by the community. In the initial rounds of NUScon our aim is to establish objective criteria for evaluating the quality of spectral reconstructions. We present here a software package for performing the quantitative analyses, and we present the results from the first two rounds of NUScon. We discuss the challenges that remain and present a roadmap for continued community-driven development with the ultimate aim of providing best practices in this rapidly evolving field. The NUScon software package and all data from evaluating the challenge problems are hosted on the NMRbox platform.

Nonuniform Sampling for NMR Spectroscopy.

Nonuniform sampling was first proposed more than 40 years ago as an alternate method for sampling two-dimensional NMR data was initially pursued by only a small number of scientists. However, it has been gradually adopted after it was shown that major gains in measuring time and spectrum resolution can be obtained. Furthermore, migration of NMR software to the Unix environment facilitated development of new processing tools, and there is now a selection of programs available that yield high-quality reconstructions of NUS data. Moreover, it became obvious that recording high-resolution 3D and 4D protein NMR spectra at the resolution provided by modern high-field instruments was not possible with uniform sampling. It has become apparent that sparse, low dynamic-range NMR spectra, in particular, the triple resonance experiments are all best recorded with NUS. Optimal sampling schedules can yield benefits with respect to detecting weak peaks in high dynamic-range spectra and therefore a careful use of 2D HSQC-like spectra of mixed concentrations of small molecules is feasible. It is not yet clear whether crowded high dynamic-range spectra, such as NOESYs with many cross-peaks, benefit from NUS. On the other hand, NUS appears to be the best option for recording such high dynamic-range spectra if crowding can be reduced by shorten NOESY mixing times and/or by reducing overlap through isotopic labeling in high-resolution 3D and 4D experiments. Here we discuss principals and applications of the method, trying to provide a wide overview, but are biased by our own approaches. Thus, we will obviously miss important developments elsewhere and do not claim to be comprehensive.

Mixed pyruvate labeling enables backbone resonance assignment of large proteins using a single experiment.

Backbone resonance assignment is a critical first step in the investigation of proteins by NMR. This is traditionally achieved with a standard set of experiments, most of which are not optimal for large proteins. Of these, HNCA is the most sensitive experiment that provides sequential correlations. However, this experiment suffers from chemical shift degeneracy problems during the assignment procedure. We present a strategy that increases the effective resolution of HNCA and enables near-complete resonance assignment using this single HNCA experiment. We utilize a combination of 2-13C and 3-13C pyruvate as the carbon source for isotope labeling, which suppresses the one bond (1Jαß) coupling providing enhanced resolution for the Cα resonance and amino acid-specific peak shapes that arise from the residual coupling. Using this approach, we can obtain near-complete (>85%) backbone resonance assignment of a 42 kDa protein using a single HNCA experiment.

Interpolating and extrapolating with hmsIST: seeking a tmax for optimal sensitivity, resolution and frequency accuracy.

Non-Uniform Sampling has the potential to exploit the optimal resolution of high-field NMR instruments. This is not possible in 3D and 4D NMR experiments when using traditional uniform sampling due to the long overall measurement time. Nominally, uniformly sampled time domain data acquired to a maximum evolution time tmax can be extended to high resolution via a virtual maximum evolution time t*max while extrapolating with linear prediction or iterative soft thresholding (IST). At the high resolution obtainable with extrapolation of US data, however, the accuracy of peak positions is compromised as observed when comparing inter- and intra-residue peaks in a 3D HNCA experiment. However, the accuracy of peak positions is largely improved by spreading the same number of acquired time domain data points non-uniformly over a larger evolution time to an optimal tmax followed by extrapolation to a total t*max and processing the data with an appropriate reconstruction method, such as hmsIST. To explore the optimum value of experimentally measured tmax to be reached non-uniformly with a given number of sampling points we have created test situations of time-equivalent experiments and evaluate sensitivity and accuracy of peak positions. Here we use signal-to-maximum-noise ratio as the decisive measure of sensitivity. We find that both sensitivity and resolution are optimal when PoissonGap sampling to a tmax of about ½*T2*. Digital resolution is further enhanced by extrapolating the range of acquired time domain data to 2*T2* but without measuring experimental points beyond ½*T2*.

Carbon Isotopomer Analysis with Non-Unifom Sampling HSQC NMR for Cell Extract and Live Cell Metabolomics Studies.

Isotopomer analysis using either 13C NMR or LC/GC-MS has been an invaluable tool for studying metabolic activities in a variety of systems. Traditional challenges are, however, that 13C-detected NMR is insensitive despite its high resolution, and that MS-based techniques cannot easily differentiate positional isotopomers. In addition, current 13C NMR or LC/GC-MS has limitations in detecting metabolites in living cells. Here, we describe a non-uniform sampling-based 2D heteronuclear single quantum coherence (NUS HSQC) approach to measure metabolic isotopomers in both cell lysates and living cells. The method provides a high resolution that can resolve multiplet structures in the 13C dimension while retaining the sensitivity of the 1H-indirect detection. The approach was tested in L1210 mouse leukemia cells labeled with 13C acetate by measuring NUS HSQC with 25% sampling density. The results gave a variety of metabolic information such as (1) higher usage of acetate in acetylation pathway than aspartate synthesis, (2) TCA cycle efficiency changes upon the inhibition of mitochondrial oxidative phosphorylation by pharmacological agents, and (3) position-dependent isotopomer patterns in fatty acids in living cells. In addition, we were able to detect fatty acids along with other hydrophilic molecules in one sample of live cells without extraction. Overall, the high sensitivity and resolution along with the application to live cells should make the NUS HSQC approach attractive in studying carbon flux information in metabolic studies.

Solid-state NMR structure determination from diagonal-compensated, sparsely nonuniform-sampled 4D proton-proton restraints.

We report acquisition of diagonal-compensated protein structural restraints from four-dimensional solid-state NMR spectra on extensively deuterated and (1)H back-exchanged proteins. To achieve this, we use homonuclear (1)H-(1)H correlations with diagonal suppression and nonuniform sampling (NUS). Suppression of the diagonal allows the accurate identification of cross-peaks which are otherwise obscured by the strong autocorrelation or whose intensity is biased due to partial overlap with the diagonal. The approach results in unambiguous spectral interpretation and relatively few but reliable restraints for structure calculation. In addition, the diagonal suppression produces a spectrum with low dynamic range for which ultrasparse NUS data sets can be readily reconstructed, allowing straightforward application of NUS with only 2% sampling density with the advantage of more heavily sampling time-domain regions of high signal intensity. The method is demonstrated here for two proteins, α-spectrin SH3 microcrystals and hydrophobin functional amyloids. For the case of SH3, suppression of the diagonal results in facilitated identification of unambiguous restraints and improvement of the quality of the calculated structural ensemble compared to nondiagonal-suppressed 4D spectra. For the only partly assigned hydrophobin rodlets, the structure is yet unknown. Applied to this protein of biological significance with large inhomogeneous broadening, the method allows identification of unambiguous crosspeaks that are otherwise obscured by the diagonal.

Selective methyl labeling of eukaryotic membrane proteins using cell-free expression.

Structural characterization of membrane proteins and other large proteins with NMR relies increasingly on perdeuteration combined with incorporation of specifically protonated amino acid moieties, such as methyl groups of isoleucines, valines, or leucines. The resulting proton dilution reduces dipolar broadening producing sharper resonance lines, ameliorates spectral crowding, and enables measuring of crucial distances between and to methyl groups. While incorporation of specific methyl labeling is now well established for bacterial expression using suitable precursors, corresponding methods are still lacking for cell-free expression, which is often the only choice for producing labeled eukaryotic membrane proteins in mg quantities. Here we show that we can express methyl-labeled human integral membrane proteins cost-effectively by cell-free expression based of crude hydrolyzed ILV-labeled OmpX inclusion bodies. These are obtained in Escherichia coli with very high quantity and represent an optimal intermediate to channel ILV precursors into the eukaryotic proteins.

Perspectives in magnetic resonance: NMR in the post-FFT era.

Multi-dimensional NMR spectra have traditionally been processed with the fast Fourier transformation (FFT). The availability of high field instruments, the complexity of spectra of large proteins, the narrow signal dispersion of some unstructured proteins, and the time needed to record the necessary increments in the indirect dimensions to exploit the resolution of the highfield instruments make this traditional approach unsatisfactory. New procedures need to be developed beyond uniform sampling of the indirect dimensions and reconstruction methods other than the straight FFT are necessary. Here we discuss approaches of non-uniform sampling (NUS) and suitable reconstruction methods. We expect that such methods will become standard for multi-dimensional NMR data acquisition with complex biological macromolecules and will dramatically enhance the power of modern biological NMR.

Exploring signal-to-noise ratio and sensitivity in non-uniformly sampled multi-dimensional NMR spectra.

It is well established that non-uniform sampling (NUS) allows acquisition of multi-dimensional NMR spectra at a resolution that cannot be obtained with traditional uniform acquisition through the indirect dimensions. However, the impact of NUS on the signal-to-noise ratio (SNR) and sensitivity are less well documented. SNR and sensitivity are essential aspects of NMR experiments as they define the quality and extent of data that can be obtained. This is particularly important for spectroscopy with low concentration samples of biological macromolecules. There are different ways of defining the SNR depending on how to measure the noise, and the distinction between SNR and sensitivity is often not clear. While there are defined procedures for measuring sensitivity with high concentration NMR standards, such as sucrose, there is no clear or generally accepted definition of sensitivity when comparing different acquisition and processing methods for spectra of biological macromolecules with many weak signals close to the level of noise. Here we propose tools for estimating the SNR and sensitivity of NUS spectra with respect to sampling schedule and reconstruction method. We compare uniformly acquired spectra with NUS spectra obtained in the same total measuring time. The time saving obtained when only 1/k of the Nyquist grid points are sampled is used to measure k-fold more scans per increment. We show that judiciously chosen NUS schedules together with suitable reconstruction methods can yield a significant increase of the SNR within the same total measurement time. Furthermore, we propose to define the sensitivity as the probability to detect weak peaks and show that time-equivalent NUS can considerably increase this detection sensitivity. The sensitivity gain increases with the number of NUS indirect dimensions. Thus, well-chosen NUS schedules and reconstruction methods can significantly increase the information content of multidimensional NMR spectra of challenging biological macromolecules.

The C-terminal domain of eukaryotic initiation factor 5 promotes start codon recognition by its dynamic interplay with eIF1 and eIF2ß.

Recognition of the proper start codon on mRNAs is essential for protein synthesis, which requires scanning and involves eukaryotic initiation factors (eIFs) eIF1, eIF1A, eIF2, and eIF5. The carboxyl terminal domain (CTD) of eIF5 stimulates 43S preinitiation complex (PIC) assembly; however, its precise role in scanning and start codon selection has remained unknown. Using nuclear magnetic resonance (NMR) spectroscopy, we identified the binding sites of eIF1 and eIF2ß on eIF5-CTD and found that they partially overlapped. Mutating select eIF5 residues in the common interface specifically disrupts interaction with both factors. Genetic and biochemical evidence indicates that these eIF5-CTD mutations impair start codon recognition and impede eIF1 release from the PIC by abrogating eIF5-CTD binding to eIF2ß. This study provides mechanistic insight into the role of eIF5-CTD's dynamic interplay with eIF1 and eIF2ß in switching PICs from an open to a closed state at start codons.

Application of iterative soft thresholding for fast reconstruction of NMR data non-uniformly sampled with multidimensional Poisson Gap scheduling.

The fast Fourier transformation has been the gold standard for transforming data from time to frequency domain in many spectroscopic methods, including NMR. While reliable, it has as a drawback that it requires a grid of uniformly sampled data points. This needs very long measuring times for sampling in multidimensional experiments in all indirect dimensions uniformly and even does not allow reaching optimal evolution times that would match the resolution power of modern high-field instruments. Thus, many alternative sampling and transformation schemes have been proposed. Their common challenges are the suppression of the artifacts due to the non-uniformity of the sampling schedules, the preservation of the relative signal amplitudes, and the computing time needed for spectra reconstruction. Here we present a fast implementation of the Iterative Soft Thresholding approach (istHMS) that can reconstruct high-resolution non-uniformly sampled NMR data up to four dimensions within a few hours and make routine reconstruction of high-resolution NUS 3D and 4D spectra convenient. We include a graphical user interface for generating sampling schedules with the Poisson-Gap method and an estimation of optimal evolution times based on molecular properties. The performance of the approach is demonstrated with the reconstruction of non-uniformly sampled medium and high-resolution 3D and 4D protein spectra acquired with sampling densities as low as 0.8%. The method presented here facilitates acquisition, reconstruction and use of multidimensional NMR spectra at otherwise unreachable spectral resolution in indirect dimensions.

Applications of non-uniform sampling and processing.

Modern high-field NMR instruments provide unprecedented resolution. To make use of the resolving power in multidimensional NMR experiment standard linear sampling through the indirect dimensions to the maximum optimal evolution times (~1.2T (2)) is not practical because it would require extremely long measurement times. Thus, alternative sampling methods have been proposed during the past 20 years. Originally, random nonlinear sampling with an exponentially decreasing sampling density was suggested, and data were transformed with a maximum entropy algorithm (Barna et al., J Magn Reson 73:69-77, 1987). Numerous other procedures have been proposed in the meantime. It has become obvious that the quality of spectra depends crucially on the sampling schedules and the algorithms of data reconstruction. Here we use the forward maximum entropy (FM) reconstruction method to evaluate several alternate sampling schedules. At the current stage, multidimensional NMR spectra that do not have a serious dynamic range problem, such as triple resonance experiments used for sequential assignments, are readily recorded and faithfully reconstructed using non-uniform sampling. Thus, these experiments can all be recorded non-uniformly to utilize the power of modern instruments. On the other hand, for spectra with a large dynamic range, such as 3D and 4D NOESYs, choosing optimal sampling schedules and the best reconstruction method is crucial if one wants to recover very weak peaks. Thus, this chapter is focused on selecting the best sampling schedules and processing methods for high-dynamic range spectra.

Metabolic regulation of protein N-alpha-acetylation by Bcl-xL promotes cell survival.

Previous experiments suggest a connection between the N-alpha-acetylation of proteins and sensitivity of cells to apoptotic signals. Here, we describe a biochemical assay to detect the acetylation status of proteins and demonstrate that protein N-alpha-acetylation is regulated by the availability of acetyl-CoA. Because the antiapoptotic protein Bcl-xL is known to influence mitochondrial metabolism, we reasoned that Bcl-xL may provide a link between protein N-alpha-acetylation and apoptosis. Indeed, Bcl-xL overexpression leads to a reduction in levels of acetyl-CoA and N-alpha-acetylated proteins in the cell. This effect is independent of Bax and Bak, the known binding partners of Bcl-xL. Increasing cellular levels of acetyl-CoA by addition of acetate or citrate restores protein N-alpha-acetylation in Bcl-xL-expressing cells and confers sensitivity to apoptotic stimuli. We propose that acetyl-CoA serves as a signaling molecule that couples apoptotic sensitivity to metabolism by regulating protein N-alpha-acetylation.

High-resolution 3D CANCA NMR experiments for complete mainchain assignments using C(alpha) direct detection.

The primary limitation of solution state NMR with larger, highly dynamic, or paramagnetic systems originates from signal losses due to fast transverse relaxation. This is related to the high gyromagnetic ratio gamma of protons, which are usually detected. Thus, it is attractive to consider detection of nuclei with lower gamma, such as (13)C, for extending the size limits of NMR. Here, we present an approach for complete assignment of C(alpha) and N resonances in fast relaxing proteins using a C(alpha) detected 3D CANCA experiment for perdeuterated proteins. The CANCA experiment correlates alpha carbons with the sequentially adjacent and succeeding nitrogen and alpha carbons. This enables elongation of the chain of assigned residues simply by navigating along both nitrogen and carbon dimensions using a "stairway" assignment procedure. The simultaneous use of both C(alpha) and N sequential connectivities makes the experiment more robust than conventional 3D experiments, which rely solely on a single (13)C indirect dimension for sequential information. The 3D CANCA experiment, which is very useful for mainchain assignments of higher molecular weight proteins at high magnetic field, also provides an attractive alterative for smaller proteins. Two versions of the experiment are described for samples that are (13)C labeled either uniformly or at alternate positions for removing one-bond (13)C-(13)C couplings. To achieve both high resolution and sensitivity, extensive nonuniform sampling was employed. Adding longitudinal relaxation enhancement agents can allow for shorter recycling delays, decreased measuring time, or enhanced sensitivity.

Poisson-gap sampling and forward maximum entropy reconstruction for enhancing the resolution and sensitivity of protein NMR data.

The Fourier transform has been the gold standard for transforming data from the time domain to the frequency domain in many spectroscopic methods, including NMR spectroscopy. While reliable, it has the drawback that it requires a grid of uniformely sampled data points, which is not efficient for decaying signals, and it also suffers from artifacts when dealing with nondecaying signals. Over several decades, many alternative sampling and transformation schemes have been proposed. Their common problem is that relative signal amplitudes are not well-preserved. Here we demonstrate the superior performance of a sine-weighted Poisson-gap distribution sparse-sampling scheme combined with forward maximum entropy (FM) reconstruction. While the relative signal amplitudes are well-preserved, we also find that the signal-to-noise ratio is enhanced up to 4-fold per unit of data acquisition time relative to traditional linear sampling.

FM reconstruction of non-uniformly sampled protein NMR data at higher dimensions and optimization by distillation.

Non-uniform sampling (NUS) enables recording of multidimensional NMR data at resolutions matching the resolving power of modern instruments without using excessive measuring time. However, in order to obtain satisfying results, efficient reconstruction methods are needed. Here we describe an optimized version of the Forward Maximum entropy (FM) reconstruction method, which can reconstruct up to three indirect dimensions. For complex datasets, such as NOESY spectra, the performance of the procedure is enhanced by a distillation procedure that reduces artifacts stemming from intense peaks.

PDCD4 inhibits translation initiation by binding to eIF4A using both its MA3 domains.

Programmed Cell Death 4 (PDCD4) is a protein known to bind eukaryotic initiation factor 4A (eIF4A), inhibit translation initiation, and act as a tumor suppressor. PDCD4 contains two C-terminal MA3 domains, which are thought to be responsible for its inhibitory function. Here, we analyze the structures and inhibitory functions of these two PDCD4 MA3 domains by x-ray crystallography, NMR, and surface plasmon resonance. We show that both MA3 domains are structurally and functionally very similar and bind specifically to the eIF4A N-terminal domain (eIF4A-NTD) using similar binding interfaces. We found that the PDCD4 MA3 domains compete with the eIF4G MA3 domain and RNA for eIF4A binding. Our data provide evidence that PDCD4 inhibits translation initiation by displacing eIF4G and RNA from eIF4A. The PDCD4 MA3 domains act synergistically to form a tighter and more stable complex with eIF4A, which explains the need for two tandem MA3 domains.

Ultrahigh-resolution (1)H-(13)C HSQC spectra of metabolite mixtures using nonlinear sampling and forward maximum entropy reconstruction.

To obtain a comprehensive assessment of metabolite levels from extracts of leukocytes, we have recorded ultrahigh-resolution 1H-13C HSQC NMR spectra of cell extracts, which exhibit spectral signatures of numerous small molecules. However, conventional acquisition of such spectra is time-consuming and hampers measurements on multiple samples, which would be needed for statistical analysis of metabolite concentrations. Here we show that the measurement time can be dramatically reduced without loss of spectral quality when using nonlinear sampling (NLS) and a new high-fidelity forward maximum-entropy (FM) reconstruction algorithm. This FM reconstruction conserves all measured time-domain data points and guesses the missing data points by an iterative process. This consists of discrete Fourier transformation of the sparse time-domain data set, computation of the spectral entropy, determination of a multidimensional entropy gradient, and calculation of new values for the missing time-domain data points with a conjugate gradient approach. Since this procedure does not alter measured data points, it reproduces signal intensities with high fidelity and does not suffer from a dynamic range problem. As an example we measured a natural abundance 1H-13C HSQC spectrum of metabolites from granulocyte cell extracts. We show that a high-resolution 1H-13C HSQC spectrum with 4k complex increments recorded linearly within 3.7 days can be reconstructed from one-seventh of the increments with nearly identical spectral appearance, indistinguishable signal intensities, and comparable or even lower root-mean-square (rms) and peak noise patterns measured in signal-free areas. Thus, this approach allows recording of ultrahigh resolution 1H-13C HSQC spectra in a fraction of the time needed for recording linearly sampled spectra.

Mapping of the auto-inhibitory interactions of protein kinase R by nuclear magnetic resonance.

The dsRNA-dependent protein kinase (PKR) is a key mediator of the anti-viral and anti-proliferative effects of interferon. Unphosphorylated PKR is characterized by inhibitory interactions between the kinase and RNA binding domains (RBDs), but the structural details of the latent state and its unraveling during activation are not well understood. To study PKR regulation by NMR we assigned a large portion of the backbone resonances of the catalytically inactive K296R kinase domain, and performed (15)N-heteronuclear single quantum coherence (HSQC) titrations of this kinase domain with the RBDs. Chemical shift perturbations in the kinase indicate that RBD2 binds to the substrate eIF2alpha docking site in the kinase C-lobe. Consistent with these results, a mutation in the eIF2alpha docking site, F495A, displays weaker interactions with the RBD. The full-length RBD1+2 binds more strongly to the kinase domain than RBD2 alone. The observed chemical shift changes extend from the eIF2alpha binding site into the kinase N-lobe and inside the active site, consistent with weak interactions between the N-terminal part of the RBD and the kinase.