Optimised collection of non-uniformly sampled 2D-HSQC NMR spectra for use in metabolic flux analysis

Nuclear magnetic resonance (NMR) spectroscopy is integral to metabolic studies; yet, it can suffer from the long acquisition times required to collect data of sufficient signal strength and resolution. The use of non-uniform sampling (NUS) allows faster collection of NMR spectra without loss of spectral integrity. When planning experimental methodologies to perform metabolic flux analysis (MFA) of cell metabolism, a variety of options are available for the acquisition of NUS NMR data. Before beginning data collection, decisions have to be made regarding selection of pulse sequence, number of transients and NUS specific parameters such as the sampling level and sampling schedule. Poor choices will impact data quality, which may have a negative effect on the subsequent analysis and biological interpretation. Herein, we describe factors that should be considered when setting up non-uniformly sampled 2D-¹ H,¹³ C HSQC NMR experiments for MFA and provide a standard protocol for users to follow.

Documentation and on farm conservation of neglected and underutilized plant species in Lamjung district, Nepal

Neglected and underutilized species (NUS) are proven superfoods, but still many of those species are not mainstreamed in our food system. In this regard, research was carried out to explore diversity and identify prioritized species, explore use-values, and identify the role of a socio-demographic factor in its conservation and promotion. For this, a survey was conducted at two rural municipalities' viz. Marsayndi Rural Municipality-01 (Ghanpokhara) and Kwhlosothar Rural Municipality (ward no-03, Ghalegaun & ward no-04, Bhujung) in Lamjung district of Nepal. Location wise cluster sampling was conducted for data collection and the techniques employed were direct field observation, household sampling, key informant interview, personal interviews, and field studies. 92 species were documented during the study, moreover, a significant role of socio-demographic factors was seen in characterizing, evaluating, and conserving NUS on-farm. The results indicated that the education status and primary occupation of the household head had a major role whereas ethnicity had a certain level of the role while gender had no role to play on on-farm conservation of NUS. People with basic education status and agriculture as their primary occupations showed a higher influence on conservation. The result concludes with some insight on the way forward for NUS and addresses a need to establish a research and development program including all potential participants such as with government, academics, entrepreneurs, and producers to promote NUS.

Reducing the measurement time of exact NOEs by non-uniform sampling

We have previously reported on the measurement of exact NOEs (eNOEs), which yield a wealth of additional information in comparison to conventional NOEs. We have used these eNOEs in a variety of applications, including calculating high-resolution structures of proteins and RNA molecules. The collection of eNOEs is challenging, however, due to the need to measure a NOESY buildup series consisting of typically four NOESY spectra with varying mixing times in a single measurement session. While the 2D version can be completed in a few days, a fully sampled 3D-NOESY buildup series can take 10 days or more to acquire. This can be both expensive as well as problematic in the case of samples that are not stable over such a long period of time. One potential method to significantly decrease the required measurement time of eNOEs is to use non-uniform sampling (NUS) to decrease the number of points measured in the indirect dimensions. The effect of NUS on the extremely tight distance restraints extracted from eNOEs may be very pronounced. Therefore, we investigated the fidelity of eNOEs measured from three test cases at decreasing NUS densities: the 18.4 kDa protein human Pin1, the 4.1 kDa WW domain of Pin1 (both in 3D), and a 4.6 kDa 14mer RNA UUCG tetraloop (2D). Our results show that NUS imparted negligible error on the eNOE distances derived from good quality data down to 10% sampling for all three cases, but there is a noticeable decrease in the eNOE yield that is dependent upon the underlying sparsity, and thus complexity, of the sample. For Pin1, this transition occurred at roughly 40% while for the WW domain and the UUCG tetraloop it occurred at lower NUS densities of 20% and 10%, respectively. We rationalized these numbers through reconstruction simulations under various conditions. The extent of this loss depends upon the number of scans taken as well as the number of peaks to be reconstructed. Based on these findings, we have created guidelines for choosing an optimal NUS density depending on the number of peaks needed to be reconstructed in the densest region of a 2D or 3D NOESY spectrum.

Developing nonuniform sampling strategies to improve sensitivity and resolution in 1,1-ADEQUATE experiments

Nonuniform sampling (NUS) strategies are developed for acquiring highly resolved 1,1-ADEQUATE spectra, in both conventional and homodecoupled (HD) variants with improved sensitivity. Specifically, the quantile-directed and Poisson gap methods were critically compared for distributing the samples nonuniformly, and the quantile schedules were further optimized for weighting. Both maximum entropy and iterative soft thresholding spectral estimation algorithms were evaluated. All NUS approaches were robust when the degree of data reduction is moderate, on the order of a 50% reduction of sampling points. Further sampling reduction by NUS is facilitated by using weighted schedules designed by the quantile method, which also suppresses sampling noise well. Seed independence and the ability to specify the sample weighting in quantile scheduling are important in optimizing NUS for 1,1-ADEQUATE data acquisition. Using NUS yields an improvement in sensitivity, while also making longer evolution times accessible that would be difficult or impractical to attain by uniform sampling. Theoretical predictions for the sensitivity enhancements in these experiments are in the range of 5-20%; NUS is shown to disambiguate weak signals, reveal some ⁿ J_CC correlations obscured by noise, and improve signal strength relative to uniform sampling in the same experimental time. This work presents sample schedule development for applying NUS to challenging experiments. The schedules developed here are made available for general use and should facilitate the broader utilization of ADEQUATE experiments (including 1,1-, 1,n-, and HD- variants) for challenging structure elucidation problems.

Triplet NOAH supersequences optimised for small molecule structure characterisation

A series of NMR supersequences are presented for the time-efficient structure characterisation of small molecules in the solution state. These triplet sequences provide HMBC, HSQC, and one homonuclear correlation experiment of choice according to the NMR by Ordered Acquisition using ¹ H detection principle. The experiments are demonstrated to be compatible with non-uniform sampling schemes and may be acquired and processed under full automation.

Non-uniform HYSCORE: Measurement, processing and analysis with Hyscorean

Non-uniform sampling (NUS) provides a considerable reduction of measurement time especially for multi-dimensional experiments. This comes at the cost of additional signal processing steps to reconstruct the complete signal from the experimental data points. Despite being routinely employed in NMR for many experiments, EPR applications have not benefited from NUS due to the lack of a straightforward implementation to perform NUS in common commercial spectrometers. In this work we present a novel method to perform NUS HYSCORE experiments on commercial Bruker EPR spectrometers, along with a benchmark of modern reconstruction methods, and new processing software tools for NUS HYSCORE signals. All of this comes in the form of a free-software package: Hyscorean. Experimental NUS spectra are measured and processed with this package using different reconstruction methods and compared to their uniform sampled counterparts, thereby showcasing the method's potential for EPR spectroscopy.

A Deeper Investigation of Drug Degradation Mixtures Using a Combination of MS and NMR Data: Application to Indapamide

A global approach that is based on a combination of mass spectrometry (MS) and nuclear magnetic resonance (NMR) data has been developed for a complete and rapid understanding of drug degradation mixtures. We proposed a workflow based on a sample preparation protocol that is compatible to MS and NMR, the selection of the most appropriate experiments for each technique, and the implementation of prediction software and multivariable analysis method for a better interpretation and correlation of MS and NMR spectra. We have demonstrated the efficient quantification of the remaining active pharmaceutical ingredient (API). The unambiguous characterization of degradation products (DPs) was reached while using the potential of ion mobility-mass spectrometry (IM-MS) for fragment ions filtering (HDMS^E) and the implementation of two-dimensional (2D) NMR experiments with the non-uniform sampling (NUS) method. We have demonstrated the potential of quantitative NMR (qNMR) for the estimation of low level DPs. Finally, in order to simultaneously monitor multi-samples, the contribution of partial least squares (PLS) regression was evaluated. Our methodology was tested on three indapamide forced degradation conditions (acidic, basic, and oxidative) and it could be easily transposed in the drug development field to assist in the interpretation of complex mixtures (stability studies, impurities profiling, and biotransformation screening).

Improving the sensitivity of FT-NMR spectroscopy by apodization weighted sampling

Apodization weighted acquisition is a simple approach to enhance the sensitivity of multidimensional NMR spectra by scaling the number of scans during acquisition of the indirect dimension(s). The signal content of the resulting spectra is identical to conventionally sampled data, yet the spectra show improved signal-to-noise ratios. There are no special requirements for data acquisition and processing: the time-domain data can be transformed with the same schemes used for conventionally recorded spectra, including Fourier transformation. The method is of general use in multidimensional liquid and solid state NMR experiments if the number of recorded transients per sampling point is bigger than the minimum required phase cycle of the pulse sequence.

Compressed NMR: Combining compressive sampling and pure shift NMR techniques

Historically, the resolution of multidimensional nuclear magnetic resonance (NMR) has been orders of magnitude lower than the intrinsic resolution that NMR spectrometers are capable of producing. The slowness of Nyquist sampling as well as the existence of signals as multiplets instead of singlets have been two of the main reasons for this underperformance. Fortunately, two compressive techniques have appeared that can overcome these limitations. Compressive sensing, also known as compressed sampling (CS), avoids the first limitation by exploiting the compressibility of typical NMR spectra, thus allowing sampling at sub-Nyquist rates, and pure shift techniques eliminate the second issue "compressing" multiplets into singlets. This paper explores the possibilities and challenges presented by this combination (compressed NMR). First, a description of the CS framework is given, followed by a description of the importance of combining it with the right pure shift experiment. Second, examples of compressed NMR spectra and how they can be combined with covariance methods will be shown.

DNA barcoding to promote social awareness and identity of neglected, underutilized plant species having valuable nutritional properties

It is estimated that about 7000 plant species and a large number of cultivars and varieties have been cultivated for consumption in human history. However, <0.5% of these currently provide the majority of human food energy needs worldwide (e.g., rice, wheat, maize, and potato). Global issues such as climate change, diffusion of pests, and resistance to agrochemical treatments are posing great concern about the sustainable cultivation of these major staples, especially in equatorial and tropical countries, such as Sub Saharan Africa. In addition, most of these regions contain malnutrition and micronutrient deficiencies, and the sum of such problems create serious implications at social, political, and economic levels. A possible solution relies on the exploitation of plant biodiversity and particularly on the so-called NUS (Neglected and Underutilized Species). These plants are traditionally grown in their centres of origin and continue to be maintained by sociocultural preferences, however they remain inadequately documented and neglected by formal research and conservation programs. Although they are important in terms of micronutrients and the ability to grow in harsh conditions, these species are falling into disuse due to agronomic, genetic, economic, and cultural reasons. To promote and spread their cultivation at the global scale, along with knowledge on their suitability for human nutrition, reliable identification systems are necessary to guarantee adequate authenticity along the entire supply chain and distribution network. A precise identification of the different species and their varieties is fundamental both to retrieve information on their origin and authenticate the raw materials (i.e., seeds, leaves and fruit) and related processed products that can be distributed at the local or global scale. DNA-based techniques can help achieve this mission. In particular, the DNA barcoding approach has gained a role of primary importance due to its universality and versatility. Here, we discuss the advantages in using DNA barcoding for the identification of some of the most representative NUS species, as well as their traceability and conservation of cultural practices around them.

13C APSY-NMR for sequential assignment of intrinsically disordered proteins

The increasingly recognized biological relevance of intrinsically disordered proteins requires a continuous expansion of the tools for their characterization via NMR spectroscopy, the only technique so far able to provide atomic-resolution information on these highly mobile macromolecules. Here we present the implementation of projection spectroscopy in ¹³C-direct detected NMR experiments to achieve the sequence specific assignment of IDPs. The approach was used to obtain the complete backbone assignment at high temperature of α-synuclein, a paradigmatic intrinsically disordered protein.

Measurement of protein backbone 13CO and 15N relaxation dispersion at high resolution

Peak overlap in crowded regions of two-dimensional spectra prevents characterization of dynamics for many sites of interest in globular and intrinsically disordered proteins. We present new three-dimensional pulse sequences for measurement of Carr-Purcell-Meiboom-Gill relaxation dispersions at backbone nitrogen and carbonyl positions. To alleviate increase in the measurement time associated with the additional spectral dimension, we use non-uniform sampling in combination with two distinct methods of spectrum reconstruction: compressed sensing and co-processing with multi-dimensional decomposition. The new methodology was validated using disordered protein CD79A from B-cell receptor and an SH3 domain from Abp1p in exchange between its free form and bound to a peptide from the protein Ark1p. We show that, while providing much better resolution, the 3D NUS experiments give the similar accuracy and precision of the dynamic parameters to ones obtained using traditional 2D experiments. Furthermore, we show that jackknife resampling of the spectra yields robust estimates of peak intensities errors, eliminating the need for recording duplicate data points.

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 t_max 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 t_max 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 t_max 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 t_max 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^*.

Sparse multidimensional iterative lineshape-enhanced (SMILE) reconstruction of both non-uniformly sampled and conventional NMR data

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.

Deterministic multidimensional nonuniform gap sampling

Born from empirical observations in nonuniformly sampled multidimensional NMR data relating to gaps between sampled points, the Poisson-gap sampling method has enjoyed widespread use in biomolecular NMR. While the majority of nonuniform sampling schemes are fully randomly drawn from probability densities that vary over a Nyquist grid, the Poisson-gap scheme employs constrained random deviates to minimize the gaps between sampled grid points. We describe a deterministic gap sampling method, based on the average behavior of Poisson-gap sampling, which performs comparably to its random counterpart with the additional benefit of completely deterministic behavior. We also introduce a general algorithm for multidimensional nonuniform sampling based on a gap equation, and apply it to yield a deterministic sampling scheme that combines burst-mode sampling features with those of Poisson-gap schemes. Finally, we derive a relationship between stochastic gap equations and the expectation value of their sampling probability densities.

Toward optimal-resolution NMR of intrinsically disordered proteins

Proteins, which, in their native conditions, sample a multitude of distinct conformational states characterized by high spatiotemporal heterogeneity, most often termed as intrinsically disordered proteins (IDPs), have become a target of broad interest over the past 15years. With the growing evidence of their important roles in fundamental cellular processes, there is an urgent need to characterize the conformational behavior of IDPs at the highest possible level. The unique feature of NMR spectroscopy in the context of IDPs is its ability to supply details of their structural and temporal alterations at atomic-level resolution. Here, we briefly review recently proposed NMR-based strategies to characterize transient states populated by IDPs and summarize the latest achievements and future prospects in methodological development. Because low chemical shift dispersion represents the major obstacle encountered when studying IDPs by nuclear magnetic resonance, particular attention is paid to techniques allowing one to approach the physical limits of attainable resolution.