XLSY: Extra-Large NMR Spectroscopy

Site-Specific Introduction of Alanines for the Nuclear Magnetic Resonance Investigation of Low-Complexity Regions and Large Biomolecular Assemblies

Nuclear magnetic resonance (NMR) studies of large biomolecular machines and highly repetitive proteins remain challenging due to the difficulty of assigning frequencies to individual nuclei. Here, we present an efficient strategy to address this challenge by engineering a Pyrococcus horikoshii tRNA/alanyl-tRNA synthetase pair that enables the incorporation of up to three isotopically labeled alanine residues in a site-specific manner using in vitro protein expression. The general applicability of this approach for NMR assignment has been demonstrated by introducing isotopically labeled alanines into four distinct proteins: huntingtin exon-1, HMA8 ATPase, the 300 kDa molecular chaperone ClpP, and the alanine-rich Phox2B transcription factor. For large protein assemblies, our labeling approach enabled unambiguous assignments while avoiding potential artifacts induced by site-specific mutations. When applied to Phox2B, which contains two poly-alanine tracts of nine and twenty alanines, we observed that the helical stability is strongly dependent on the homorepeat length. The capacity to selectively introduce alanines with distinct labeling patterns is a powerful tool to probe structure and dynamics of challenging biomolecular systems.

Linear discriminant analysis reveals hidden patterns in NMR chemical shifts of intrinsically disordered proteins

NMR spectroscopy is key in the study of intrinsically disordered proteins (IDPs). Yet, even the first step in such an analysis-the assignment of observed resonances to particular nuclei-is often problematic due to low peak dispersion in the spectra of IDPs. We show that the assignment process can be aided by finding "hidden" chemical shift patterns specific to the amino acid residue types. We find such patterns in the training data from the Biological Magnetic Resonance Bank using linear discriminant analysis, and then use them to classify spin systems in an α-synuclein sample prepared by us. We describe two situations in which the procedure can greatly facilitate the analysis of NMR spectra. The first involves the mapping of spin systems chains onto the protein sequence, which is part of the assignment procedure-a prerequisite for any NMR-based protein analysis. In the second, the method supports assignment transfer between similar samples. We conducted experiments to demonstrate these cases, and both times the majority of spin systems could be unambiguously assigned to the correct residue types.

Unambiguous Tracking of Protein Phosphorylation by Fast High-Resolution FOSY NMR*

Dysregulation of post-translational modifications (PTMs) like phosphorylation is often involved in disease. NMR may elucidate exact loci and time courses of PTMs at atomic resolution and near-physiological conditions but requires signal assignment to individual atoms. Conventional NMR methods for this base on tedious global signal assignment that may often fail, as for large intrinsically disordered proteins (IDPs). We present a sensitive, robust alternative to rapidly obtain only the local assignment near affected signals, based on FOcused SpectroscopY (FOSY) experiments using selective polarisation transfer (SPT). We prove its efficiency by identifying two phosphorylation sites of glycogen synthase kinase 3 beta (GSK3β) in human Tau40, an IDP of 441 residues, where the extreme spectral dispersion in FOSY revealed unprimed phosphorylation also of Ser409. FOSY may broadly benefit NMR studies of PTMs and other hotspots in IDPs, including sites involved in molecular interactions.

Multiplexing experiments in NMR and multi-nuclear MRI

Multiplexing NMR experiments by direct detection of multiple free induction decays (FIDs) in a single experiment offers a dramatic increase in the spectral information content and often yields significant improvement in sensitivity per unit time. Experiments with multi-FID detection have been designed with both homonuclear and multinuclear acquisition, and the advent of multiple receivers on commercial spectrometers opens up new possibilities for recording spectra from different nuclear species in parallel. Here we provide an extensive overview of such techniques, designed for applications in liquid- and solid-state NMR as well as in hyperpolarized samples. A brief overview of multinuclear MRI is also provided, to stimulate cross fertilization of ideas between the two areas of research (NMR and MRI). It is shown how such techniques enable the design of experiments that allow structure elucidation of small molecules from a single measurement. Likewise, in biomolecular NMR experiments multi-FID detection allows complete resonance assignment in proteins. Probes with multiple RF microcoils routed to multiple NMR receivers provide an alternative way of increasing the throughput of modern NMR systems, effectively reducing the cost of NMR analysis and increasing the information content at the same time. Solid-state NMR experiments have also benefited immensely from both parallel and sequential multi-FID detection in a variety of multi-dimensional pulse schemes. We are confident that multi-FID detection will become an essential component of future NMR methodologies, effectively increasing the sensitivity and information content of NMR measurements.

Software for reconstruction of nonuniformly sampled NMR data

Nonuniform sampling (NUS) of multidimensional NMR experiments is a powerful tool to obtain high-resolution spectra with less instrument time. With NUS, only a subset of the points needed for conventional Fourier transformation is recorded, and sophisticated algorithms are needed to reconstruct the missing data points. During the last decade, several software packages implementing the reconstruction algorithms have emerged and been refined and now result in spectra of almost similar quality as spectra from conventionally recorded and processed data. However, from the number of literature references to the reconstruction methods, many more multidimensional NMR spectra could presumably be recorded with NUS. To help researchers considering to start using NUS for their NMR experiments, we here review 13 different reconstruction methods found in five software packages (CambridgeCS, hmsIST, MddNMR, NESTA-NMR, and SMILE). We have compared how the methods run with the provided example scripts for reconstructing a nonuniform sampled three-dimensional ¹⁵ N-NOESY-HSQC at sampling densities from 5% to 50%. Overall, the spectra are all of similar quality above 20% sampling density. Thus, without any particular knowledge about the details of the reconstruction algorithms, significant reduction in the experiment time can be achieved. Below 20% sampling density, the intensities of particular weak peaks start being affected. MddNMR's IST with virtual echo and the SMILE algorithms still reproduced the spectra with the highest accuracy of peak intensities.

Novel NMR Assignment Strategy Reveals Structural Heterogeneity in Solution of the nsP3 HVD Domain of Venezuelan Equine Encephalitis Virus

In recent years, intrinsically disordered proteins (IDPs) and disordered domains have attracted great attention. Many of them contain linear motifs that mediate interactions with other factors during formation of multicomponent protein complexes. NMR spectrometry is a valuable tool for characterizing this type of interactions on both amino acid (aa) and atomic levels. Alphaviruses encode a nonstructural protein nsP3, which drives viral replication complex assembly. nsP3 proteins contain over 200-aa-long hypervariable domains (HVDs), which exhibits no homology between different alphavirus species, are predicted to be intrinsically disordered and appear to be critical for alphavirus adaptation to different cells. Previously, we have shown that nsP3 HVD of chikungunya virus (CHIKV) is completely disordered with low tendency to form secondary structures in free form. In this new study, we used novel NMR approaches to assign the spectra for the nsP3 HVD of Venezuelan equine encephalitis virus (VEEV). The HVDs of CHIKV and VEEV have no homology but are both involved in replication complex assembly and function. We have found that VEEV nsP3 HVD is also mostly disordered but contains a short stable α-helix in its C-terminal fragment, which mediates interaction with the members of cellular Fragile X syndrome protein family. Our NMR data also suggest that VEEV HVD has several regions with tendency to form secondary structures.

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.

Accelerated Nuclear Magnetic Resonance Spectroscopy with Deep Learning

Nuclear magnetic resonance (NMR) spectroscopy serves as an indispensable tool in chemistry and biology but often suffers from long experimental times. We present a proof-of-concept of the application of deep learning and neural networks for high-quality, reliable, and very fast NMR spectra reconstruction from limited experimental data. We show that the neural network training can be achieved using solely synthetic NMR signals, which lifts the prohibiting demand for a large volume of realistic training data usually required for a deep learning approach.

Fast time-resolved NMR with non-uniform sampling

NMR spectroscopy is a versatile tool for studying time-dependent processes: chemical reactions, phase transitions or macromolecular structure changes. However, time-resolved NMR is usually based on the simplest among available techniques - one-dimensional spectra serving as "snapshots" of the studied process. One of the reasons is that multidimensional experiments are very time-expensive due to costly sampling of evolution time space. In this review we summarize efforts to alleviate the problem of limited applicability of multidimensional NMR in time-resolved studies. We focus on techniques based on sparse or non-uniform sampling (NUS), which lead to experimental time reduction by omitting a significant part of the data during measurement and reconstructing it mathematically, adopting certain assumptions about the spectrum. NUS spectra are faster to acquire than conventional ones and thus better suited to the role of "snapshots", but still suffer from non-stationarity of the signal i.e. amplitude and frequency variations within a dataset. We discuss in detail how these instabilities affect the spectra, and what are the optimal ways of sampling the non-stationary FID signal. Finally, we discuss related areas of NMR where serial experiments are exploited and how they can benefit from the same NUS-based approaches.

Using Deep Neural Networks to Reconstruct Non-uniformly Sampled NMR Spectra

Non-uniform and sparse sampling of multi-dimensional NMR spectra has over the last decade become an important tool to allow for fast acquisition of multi-dimensional NMR spectra with high resolution. The success of non-uniform sampling NMR hinge on both the development of algorithms to accurately reconstruct the sparsely sampled spectra and the design of sampling schedules that maximise the information contained in the sampled data. Traditionally, the reconstruction tools and algorithms have aimed at reconstructing the full spectrum and thus 'fill out the missing points' in the time-domain spectrum, although other techniques are based on multi-dimensional decomposition and extraction of multi-dimensional shapes. Also over the last decade, machine learning, deep neural networks, and artificial intelligence have seen new applications in an enormous range of sciences, including analysis of MRI spectra. As a proof-of-principle, it is shown here that simple deep neural networks can be trained to reconstruct sparsely sampled NMR spectra. For the reconstruction of two-dimensional NMR spectra, reconstruction using a deep neural network performs as well, if not better than, the currently and widely used techniques. It is therefore anticipated that deep neural networks provide a very valuable tool for the reconstruction of sparsely sampled NMR spectra in the future to come.

Structural characterization and biological function of bivalent binding of CD2AP to intrinsically disordered domain of chikungunya virus nsP3 protein

Alphavirus nsP3 proteins contain long, intrinsically disordered, hypervariable domains, HVD, which serve as hubs for interaction with many cellular proteins. Here, we have deciphered the mechanism and function of HVD interaction with host factors in alphavirus replication. Using NMR spectroscopy, we show that CHIKV HVD contains two SH3 domain-binding sites. Using an innovative chemical shift perturbation signature approach, we demonstrate that CD2AP interaction with HVD is mediated by its SH3-A and SH3-C domains, and this leaves the SH3-B domain available for interaction with other cellular factor(s). This cooperative interaction with two SH3 domains increases binding affinity to CD2AP and possibly induces long-range allosteric effects in HVD. Our data demonstrate that BIN1, CD2AP and SH3KBP1 play redundant roles in initiation of CHIKV replication. Point mutations in both CHIKV HVD binding sites abolish its interaction with all three proteins, CD2AP, BIN1 and SH3KBP1. This results in strong inhibition of viral replication initiation.

Experiments with direct detection of multiple FIDs

Pulse schemes with direct observation of multiple free induction decays (FIDs) offer a dramatic increase in the spectral information content of NMR experiments and often yield substantial improvement in measurement sensitivity per unit time. Availability of multiple receivers on the state-of-the-art commercial spectrometers allows spectra from different nuclear species to be recorded in parallel routinely. Experiments with multi-FID detection have been designed with both, homonuclear and multinuclear acquisition. We provide a brief overview of such techniques designed for applications in liquid- and solid- state NMR as well as in hyperpolarized samples. Here we show how these techniques have led to design of experiments that allow structure elucidation of small molecules and resonance assignment in proteins from a single measurement. Probes with multiple RF micro-coils routed to multiple NMR receivers provide an alternative way of increasing the throughput of modern NMR systems. Solid-state NMR experiments have also benefited immensely from both parallel and simultaneous FID acquisition in a variety of multi-dimensional pulse schemes. We believe that multi-FID detection will become an essential component of the future NMR methodologies effectively increasing the information content of NMR experiments and reducing the cost of NMR analysis.

XLSY: Extra-Large NMR Spectroscopy

NMR studies of intrinsically disordered proteins and other complex biomolecular systems require spectra with the highest resolution and dimensionality. An efficient approach, extra‐large NMR spectroscopy, is presented for experimental data collection, reconstruction, and handling of very large NMR spectra by a combination of the radial and non‐uniform sampling, a new processing algorithm, and rigorous statistical validation. We demonstrate the first high‐quality reconstruction of a full seven‐dimensional HNCOCACONH and two five‐dimensional HACACONH and HN(CA)CONH experiments for a representative intrinsically disordered protein α‐synuclein. XLSY will significantly enhance the NMR toolbox in challenging biomolecular studies.