Efficient and economic protein labeling for NMR in mammalian expression systems: Application to a preT-cell and T-cell receptor protein.

Protein nuclear magnetic resonance (NMR) spectroscopy relies on the ability to isotopically label polypeptides, which is achieved through heterologous expression in various host organisms. Most commonly, Escherichia coli is employed by leveraging isotopically substituted ammonium and glucose to uniformly label proteins with 15N and 13C, respectively. Moreover, E. coli can grow and express proteins in uniformly deuterium-substituted water (D2O), a strategy useful for experiments targeting high molecular weight proteins. Unfortunately, many proteins, particularly those requiring specific posttranslational modifications like disulfide bonding or glycosylation for proper folding and/or function, cannot be readily expressed in their functional forms using E. coli-based expression systems. One such class of proteins includes T-cell receptors and their related preT-cell receptors. In this study, we present an expression system for isotopic labeling of proteins using a nonadherent human embryonic kidney cell line, Expi293F, and a specially designed media. We demonstrate the application of this platform to the ß subunit common to both receptors. In addition, we show that this expression system and media can be used to specifically label amino acids Phe, Ile, Val, and Leu in this system, utilizing an amino acid-specific labeling protocol that allows targeted incorporation at high efficiency without significant isotopic scrambling. We demonstrate that this system can also be used to express proteins with fluorinated amino acids. We were routinely able to obtain an NMR sample with a concentration of 200 µM from 30 mL of culture media, utilizing less than 20 mg of the labeled amino acids.

A comprehensive assessment of selective amino acid 15N-labeling in human embryonic kidney 293 cells for NMR spectroscopy.

A large proportion of human proteins contain post-translational modifications that cannot be synthesized by prokaryotes. Thus, mammalian expression systems are often employed to characterize structure/function relationships using NMR spectroscopy. Here we define the selective isotope labeling of secreted, post-translationally modified proteins using human embryonic kidney (HEK)293 cells. We determined that alpha-[15N]- atoms from 10 amino acids experience minimal metabolic scrambling (C, F, H, K, M, N, R, T, W, Y). Two more interconvert to each other (G, S). Six others experience significant scrambling (A, D, E, I, L, V). We also demonstrate that tuning culture conditions suppressed V and I scrambling. These results define expectations for 15N-labeling in HEK293 cells.

Blind assessment of monomeric AlphaFold2 protein structure models with experimental NMR data.

Recent advances in molecular modeling of protein structures are changing the field of structural biology. AlphaFold-2 (AF2), an AI system developed by DeepMind, Inc., utilizes attention-based deep learning to predict models of protein structures with high accuracy relative to structures determined by X-ray crystallography and cryo-electron microscopy (cryoEM). Comparing AF2 models to structures determined using solution NMR data, both high similarities and distinct differences have been observed. Since AF2 was trained on X-ray crystal and cryoEM structures, we assessed how accurately AF2 can model small, monomeric, solution protein NMR structures which (i) were not used in the AF2 training data set, and (ii) did not have homologous structures in the Protein Data Bank at the time of AF2 training. We identified nine open-source protein NMR data sets for such "blind" targets, including chemical shift, raw NMR FID data, NOESY peak lists, and (for 1 case) 15N-1H residual dipolar coupling data. For these nine small (70-108 residues) monomeric proteins, we generated AF2 prediction models and assessed how well these models fit to these experimental NMR data, using several well-established NMR structure validation tools. In most of these cases, the AF2 models fit the NMR data nearly as well, or sometimes better than, the corresponding NMR structure models previously deposited in the Protein Data Bank. These results provide benchmark NMR data for assessing new NMR data analysis and protein structure prediction methods. They also document the potential for using AF2 as a guiding tool in protein NMR data analysis, and more generally for hypothesis generation in structural biology research.

NMR Spectroscopy for Protein Higher Order Structure Similarity Assessment in Formulated Drug Products.

Peptide and protein drug molecules fold into higher order structures (HOS) in formulation and these folded structures are often critical for drug efficacy and safety. Generic or biosimilar drug products (DPs) need to show similar HOS to the reference product. The solution NMR spectroscopy is a non-invasive, chemically and structurally specific analytical method that is ideal for characterizing protein therapeutics in formulation. However, only limited NMR studies have been performed directly on marketed DPs and questions remain on how to quantitively define similarity. Here, NMR spectra were collected on marketed peptide and protein DPs, including calcitonin-salmon, liraglutide, teriparatide, exenatide, insulin glargine and rituximab. The 1D 1H spectral pattern readily revealed protein HOS heterogeneity, exchange and oligomerization in the different formulations. Principal component analysis (PCA) applied to two rituximab DPs showed consistent results with the previously demonstrated similarity metrics of Mahalanobis distance (DM) of 3.3. The 2D 1H-13C HSQC spectral comparison of insulin glargine DPs provided similarity metrics for chemical shift difference (Δδ) and methyl peak profile, i.e., 4 ppb for 1H, 15 ppb for 13C and 98% peaks with equivalent peak height. Finally, 2D 1H-15N sofast HMQC was demonstrated as a sensitive method for comparison of small protein HOS. The application of NMR procedures and chemometric analysis on therapeutic proteins offer quantitative similarity assessments of DPs with practically achievable similarity metrics.

Assessment of AMBER Force Fields for Simulations of ssDNA.

Single-stranded DNA (ssDNA) plays an important role in biological processes and is used in DNA nanotechnology and other novel applications. Many important research questions can be addressed with molecular simulations of ssDNA molecules; however, no dedicated force field for ssDNA has been developed, and there is limited experimental information about ssDNA structures. This study assesses the accuracy and applicability of existing Amber force fields for all-atom simulations of ssDNA, such as ff99, bsc0, bsc1, and OL15, in implicit and explicit solvents via comparison to available experimental data, such as Forster resonance energy transfer and small angle X-ray scattering. We observed that some force fields agree better with experiments than others mainly due to the difference in parameterization of the propensity for hydrogen bonding and base stacking. Overall, the Amber ff99 force field in the IGB5 or IGB8 implicit solvent and the bsc1 force field in the explicit TIP3P solvent had the best agreement with experiment.

Voxel-wise partial volume correction method for accurate estimation of tissue sodium concentration in 23 Na-MRI at 7 T.

Sodium is crucial for the maintenance of cell physiology, and its regulation of the sodium-potassium pump has implications for various neurological conditions. The distribution of sodium concentrations in tissue can be quantitatively evaluated by means of sodium MRI (23 Na-MRI). Despite its usefulness in diagnosing particular disease conditions, tissue sodium concentration (TSC) estimated from 23 Na-MRI can be strongly biased by partial volume effects (PVEs) that are induced by broad point spread functions (PSFs) as well as tissue fraction effects. In this work, we aimed to propose a robust voxel-wise partial volume correction (PVC) method for 23 Na-MRI. The method is based on a linear regression (LR) approach to correct for tissue fraction effects, but it utilizes a 3D kernel combined with a modified least trimmed square (3D-mLTS) method in order to minimize regression-induced inherent smoothing effects. We acquired 23 Na-MRI data with conventional Cartesian sampling at 7 T, and spill-over effects due to the PSF were considered prior to correcting for tissue fraction effects using 3D-mLTS. In the simulation, we found that the TSCs of gray matter (GM) and white matter (WM) were underestimated by 20% and 11% respectively without correcting tissue fraction effects, but the differences between ground truth and PVE-corrected data after the PVC using the 3D-mLTS method were only approximately 0.6% and 0.4% for GM and WM, respectively. The capability of the 3D-mLTS method was further demonstrated with in vivo 23 Na-MRI data, showing significantly lower regression errors (ie root mean squared error) as compared with conventional LR methods (p < 0.001). The results of simulation and in vivo experiments revealed that 3D-mLTS is superior for determining under- or overestimated TSCs while preserving anatomical details. This suggests that the 3D-mLTS method is well suited for the accurate determination of TSC, especially in small focal lesions associated with pathological conditions.

Quantitative Protein Disorder Assessment Using NMR Chemical Shifts.

Disorder is vital for the biological function of many proteins. The huge diversity found in disorder composition and amplitude reflects the complexity and pluripotency of intrinsically disordered proteins (IDPs). The first step toward a better understanding of IDPs is a quantitative and position-specific experimental characterization, and nuclear magnetic resonance (NMR) spectroscopy has emerged as the method of first choice. Here, we describe how to quantitatively assess the local balance between order and disorder in proteins by utilizing the Chemical shift Z-score for assessing Order/Disorder (CheZOD Z-score). This order/disorder metric is computed from the difference between experimentally determined NMR chemical shifts and computed random coil reference values. We explain in detail how CheZOD Z-scores are calculated fast and easily, either by using a python executable or by data submission to a server.

An 1H NMR study of the cytarabine degradation in clinical conditions to avoid drug waste, decrease therapy costs and improve patient compliance in acute leukemia.

Cytarabine, the 4-amino-1-(ß-D-arabinofuranosyl)-2(1H)-pyrimidinone, (ARA-C) is an antimetabolite cytidine analogue used worldwide as key drug in the management of leukaemia. As specified in the manufacturers' instructions, once the components-sterile water and cytarabine powder-are unpackaged and mixed, the solution begins to degrade after 6 hours at room temperature and 12 hours at 4°C. To evaluate how to avoid wasting the drug in short-term, low-dose treatment regimens, the reconstituted samples, stored at 25°C and 4°C, were analyzed every day of the test week by reversed-phase HPLC and high-field NMR spectroscopy. All the samples remained unchanged for the entire week, which corresponds to the time required to administer the entire commercial drug package during low-dose therapeutic regimens. The drug solution was stored in a glass container at 4°C in an ordinary freezer and drawn with sterile plastic syringes; during this period, no bacterial or fungal contamination was observed. Our findings show that an cytarabine solution prepared and stored in the original vials retains its efficacy and safety and can, therefore, be divided into small doses to be administered over more days, thus avoiding unnecessary expensive and harmful waste of the drug preparation. Moreover, patients who require daily administration of the drug could undergo the infusion at home without need to go to hospital. The stability of the aliquots would help decrease hospitalization costs.

De novo NMR pulse sequence design using Monte-Carlo optimization techniques.

Separated Local Field (SLF) experiments have been routinely used for measuring 1H-15N heteronuclear dipolar couplings in oriented-sample solid-state NMR for structure determination of proteins. In the on-going pursuit of designing better-performing SLF pulse sequences (e.g. by increasing the number of subdwells, and varying the rf amplitudes and phases), analytical treatment of the relevant average Hamiltonian terms may become cumbersome and/or nearly impossible. Numerical simulations of NMR experiments using GPU processors can be employed to rapidly calculate spectra for moderately sized spin systems, which permit an efficient numeric optimization of pulse sequences by the Monte Carlo Simulated Annealing protocol. In this work, a computational strategy was developed to find the optimal phases and timings that substantially improve the 1H-15N dipolar linewidths over a broad range of dipolar couplings as compared to SAMPI4. More than 100 pulse sequences were developed de novo and tested on an N-acetyl Leucine crystal. Seventeen distinct pulse sequences were shown to produce sharper mean linewidths than SAMPI4. Overall, these pulse sequences have more variable parameters (involving non-quadrature phases) and do not involve symmetry between the odd and even dwells, which would likely preclude their rigorous analytical treatment. The top performing pulse sequence, termed ROULETTE-1, has 18% sharper mean linewidths than SAMPI4 when run on an N-acetyl Leucine crystal. This sequence was also shown to be robust over a broad range of 1H carrier frequencies and various crystal orientations. The performance of such an optimized pulse sequence was also illustrated on 15N Leucine-labeled Pf1 coat protein reconstituted in magnetically aligned bicelles. For the optimized pulse sequence the mean peak width was 14% sharper than SAMPI4, which in turn yielded a better signal to noise ratio, 20:1 vs. 17:1. This method is potentially extendable to de novo development of a variety of NMR experiments.

A Comparison Between Emerging and Current Biophysical Methods for the Assessment of Higher-Order Structure of Biopharmaceuticals.

The higher-order structure (HOS) of protein therapeutics is a critical quality attribute directly related to their function. Traditionally, the HOS of protein therapeutics has been characterized by methods with low to medium structural resolution such as Fourier-transform infrared (FTIR), circular dichroism (CD), and intrinsic fluorescence spectroscopy, and differential scanning calorimetry (DSC). Recently, high-resolution nuclear magnetic resonance (NMR) methods have emerged as powerful tools for HOS characterization. NMR is a multi-attribute method with unique capabilities to provide information about all the structural levels of proteins in solution. We have in this study compared 1 D 1H Profile NMR with the established biophysical methods for HOS assessments using a set of blended samples of the monoclonal antibodies belonging to the subclasses IgG1 and IgG2. The study shows that Profile NMR can distinguish between most sample combinations (93%), DSC can differentiate 61% of the sample combinations, and near-ultraviolet CD spectroscopy can differentiate 52% of the sample combinations, whereas no significant distinction could be made between any samples using FTIR or intrinsic fluorescence. Our data therefore show that NMR has superior ability to address differences in HOS, a feature that could be directly applicable in comparability and similarity assessments.

Improved strategy for isoleucine 1H/13C methyl labeling in Pichia pastoris.

Site specific methyl labeling combined with methyl TROSY offers a powerful NMR approach to study structure and dynamics of proteins and protein complexes of high molecular weight. Robust and cost-effective methods have been developed for site specific protein 1H/13C methyl labeling in an otherwise deuterated background in bacteria. However, bacterial systems are not suitable for expression and isotope labeling of many eukaryotic and membrane proteins. The yeast Pichia pastoris (P. pastoris) is a commonly used host for expression of eukaryotic proteins, and site-specific methyl labeling of perdeuterated eukaryotic proteins has recently been achieved with this system. However, the practical utility of methyl labeling and deuteration in P. pastoris is limited by high costs. Here, we describe an improved method for 1H/13C-labeling of the δ-methyl group of isoleucine residues in a perdeuterated background, which reduces the cost by ≥ 50% without compromising the efficiency of isotope enrichment. We have successfully implemented this method to label actin and a G-protein coupled receptor. Our approach will facilitate studies of the structure and dynamics of eukaryotic proteins by NMR spectroscopy.

Assessment of the higher order structure of Humira®, Remicade®, Avastin®, Rituxan®, Herceptin®, and Enbrel® by 2D-NMR fingerprinting.

The advent of monoclonal antibody biosimilar products has stimulated the development of analytical methods that can better characterize an important quality attribute, namely the higher order structure (HOS). Here, we propose a simple approach based on heteronuclear 2D NMR techniques at natural abundance for generating spectral fingerprints of the HOS at high resolution. We show that the proposed method can assess the HOS of six therapeutic products, adalimumab (Humira®), bevacizumab (Avastin®), infliximab (Remicade®), rituximab (Rituxan®), trastuzumab (Herceptin®), and Etanercept (Enbrel®). After treatment with immobilized papain, the purified fragments (Fab and Fc) were analyzed by 2D proton-nitrogen and proton-carbon NMR correlations. All Fab and Fc fragments produced high-resolution 2D-NMR spectra from which assessment of their higher order structure can be performed in the context of comparability studies. In particular, the two different sequences of Fc fragments could be unambiguously distinguished. The results show that it is possible to obtain structurally dependent information at amino acid resolution of these important therapeutic agents.

Automated assignment of NMR spectra of macroscopically oriented proteins using simulated annealing.

An automated technique for the sequential assignment of NMR backbone resonances of oriented protein samples has been developed and tested based on 15N-15N homonuclear exchange and spin-exchanged separated local-field spectra. By treating the experimental spectral intensity as a pseudopotential, the Monte-Carlo Simulated Annealing algorithm has been employed to seek lowest-energy assignment solutions over a large sampling space where direct enumeration would be unfeasible. The determined sequential assignments have been scored based on the positions of the crosspeaks resulting from the possible orders for the main peaks. This approach is versatile in terms of the parameters that can be specified to achieve the best-fit result. At a minimum the algorithm requires a continuous segment of the main-peak chemical shifts obtained from a uniformly labeled sample and a spin-exchanged experimental spectrum represented as a 2D matrix array. With selective labeling experiments, groups of chemical shifts corresponding to specific locations in the protein backbone can be fixed, thereby decreasing the sampling space. The output from the program consists of a list of top-score main peak assignments, which can be subjected to further scoring criteria until a consensus solution is found. The algorithm has first been tested on a synthetic spectrum with randomly generated chemical shifts and dipolar couplings for the main peaks. The original assignments have been successfully recovered for as many as 100 main peaks when residue-type information was used even in the presence of substantial spectral peak overlap. The algorithm was then applied to assigning two sets of experimental spectra to recover and confirm the previously established assignments in an automated fashion. For the 20-residue transmembrane domain of Pf1 coat protein reconstituted in magnetically aligned bicelles, the original assignment by Park et al. (2010) was recovered by the automated algorithm with additional input from 5 selectively labeled amino acid spectra. The second case considered was the 46 residue Pf1 bacteriophage from Thiriot et al. (2005) and Knox et al. (2010), of which 38 residues were fit. Automated fitting resulted in several possible assignments but not exactly the original assignment. By using a post-fitting filtering procedure based on the number of missed cross peaks and Pf1 helical structure, a consensus spectroscopic assignment is proposed covering 84% of the original assignment. While the automated assignment works best in spectra with well-resolved crosspeaks, it also tolerates substantial spectral crowding to yield reasonable assignments in the cases where ambiguity and degeneracy of possible assignment solutions are inevitable.

Cost-effective large-scale expression of proteins for NMR studies.

We present protocols for high-level expression of isotope-labelled proteins in E. coli in cost-effective ways. This includes production of large amounts of unlabeled proteins and 13C-methyl methionine labeling in rich media, where yields of up to a gram of soluble protein per liter of culture are reached. Procedures for uniform isotope labeling of 2H, 13C and 15N using auto-induction or isopropyl-ß-D-1-thiogalactopyranoside-induction are described, with primary focus on minimal isotope consumption and high reproducibility of protein expression. These protocols are based on high cell-density fermentation, but the key procedures are easily transferred to shake flask cultures.

Theory and practice of using solvent paramagnetic relaxation enhancement to characterize protein conformational dynamics.

Paramagnetic relaxation enhancement (PRE) has been established as a powerful tool in NMR for investigating protein structure and dynamics. The PRE is usually measured with a paramagnetic probe covalently attached at a specific site of an otherwise diamagnetic protein. The present work provides the numerical formulation for probing protein structure and conformational dynamics based on the solvent PRE (sPRE) measurement, using two alternative approaches. An inert paramagnetic cosolute randomly collides with the protein, and the resulting sPRE manifests the relative solvent exposure of protein nuclei. To make the back-calculated sPRE values most consistent with the observed values, the protein structure is either refined against the sPRE, or an ensemble of conformers is selected from a pre-generated library using a Monte Carlo algorithm. The ensemble structure comprises either N conformers of equal occupancy, or two conformers with different relative populations. We demonstrate the sPRE method using GB1, a structurally rigid protein, and calmodulin, a protein comprising two domains and existing in open and closed states. The sPRE can be computed with a stand-alone program for rapid evaluation, or with the invocation of a module in the latest release of the structure calculation software Xplor-NIH. As a label-free method, the sPRE measurement can be readily integrated with other biophysical techniques. The current limitations of the sPRE method are also discussed, regarding accurate measurement and theoretical calculation, model selection and suitable timescale.

What NMR can do in the biopharmaceutical industry.

Nuclear magnetic resonance (NMR) spectroscopy has a unique capability to probe the primary and higher order molecular structure and the structural dynamics of biomolecules at an atomic resolution, and this capability has been greatly fortified over the last five decades by an astonishing NMR instrumental and methodological development. Because of these factors, NMR has become a primary tool for the structure investigation of biomolecules, spawning a whole scientific subfield dedicated to the subject. This role of NMR is by now well established and broadly appreciated, especially in the context of academic research dealing with proteins that are purified and isotope-labeled in order to facilitate the necessary sophisticated multidimensional NMR measurements. However, the more recent industrial development, manufacturing, and quality control of biopharmaceuticals provide a different framework for NMR. For example, protein drug substances are not isotope-labeled and are present in a medium of excipients, which make structural NMR measurements much more difficult. On the other hand, biotechnology involves many other analytical requirements that can be efficiently addressed by NMR. In this respect the scope and limitations of NMR are less well understood. Having the non-expert reader in mind, herein we wish to highlight the ways in which modern NMR can effectively support biotechnological developments. Our focus will be on biosimilar proteins, pointing out certain cases where its use is probably essential. Based partly on literature data, and partly on our own hands-on experience, this paper is intended to be a guide for choosing the proper NMR approach for analytical questions concerning the structural comparability of therapeutic proteins, monitoring technology-related impurities, protein quantification, analysis of spent media, identification of extractable and leachable components, etc. Also, we focus on critical considerations, particularly those coming from drug authority guidelines, which limit the use of the well-established NMR tools in everyday practice.

Assessment of dietary exposure and effect in humans: The role of NMR.

In human nutritional science progress has always depended strongly on analytical measurements for establishing relationships between diet and health. This field has undergone significant changes as a result of the development of NMR and mass spectrometry methods for large scale detection, identification and quantification of metabolites in body fluids. This has allowed systematic studies of the metabolic fingerprints that biological processes leave behind, and has become the research field of metabolomics. As a metabolic profiling technique, NMR is at its best when its unbiased nature, linearity and reproducibility are exploited in well-controlled nutritional intervention and cross-sectional population screening studies. Although its sensitivity is less good than that of mass spectrometry, NMR has maintained a strong position in metabolomics through implementation of standardisation protocols, hyphenation with mass spectrometry and chromatographic techniques, accurate quantification and spectral deconvolution approaches, and high-throughput automation. Thus, NMR-based metabolomics has contributed uniquely to new insights into dietary exposure, in particular by unravelling the metabolic fates of phytochemicals and the discovery of dietary intake markers. NMR profiling has also contributed to the understanding of the subtle effects of diet on central metabolism and lipoprotein metabolism. In order to hold its ground in nutritional metabolomics, NMR will need to step up its performance in sensitivity and resolution; the most promising routes forward are the analytical use of dynamic nuclear polarisation and developments in microcoil construction and automated fractionation.

LC-MS- and (1)H NMR-Based Metabolomic Analysis and in Vitro Toxicological Assessment of 43 Aristolochia Species.

Species of Aristolochia are used as herbal medicines worldwide. They cause aristolochic acid nephropathy (AAN), a devastating disease associated with kidney failure and renal cancer. Aristolochic acids I and II (1 and 2) are considered to be responsible for these nephrotoxic and carcinogenic effects. A wide range of other aristolochic acid analogues (AAAs) exist, and their implication in AAN may have been overlooked. An LC-MS- and (1)H NMR-based metabolomic analysis was carried out on 43 medicinally used Aristolochia species. The cytotoxicity and genotoxicity of 28 Aristolochia extracts were measured in human kidney (HK-2) cells. Compounds 1 and 2 were found to be the most common AAAs. However, AA IV (3), aristolactam I (4), and aristolactam BI (5) were also widespread. No correlation was found between the amounts of 1 or 2 and extract cytotoxicity against HK-2 cells. The genotoxicity and cytotoxicity of the extracts could be linked to their contents of 5, AA D (8), and AA IIIa (10). These results undermine the assumption that 1 and 2 are exclusively responsible for the toxicity of Aristolochia species. Other analogues are likely to contribute to their toxicity and need to be considered as nephrotoxic agents. These findings facilitate understanding of the nephrotoxic mechanisms of Aristolochia and have significance for the regulation of herbal medicines.

NMR of (133)Cs(+) in stretched hydrogels: One-dimensional, z- and NOESY spectra, and probing the ion's environment in erythrocytes.

(133)Cs nuclear magnetic resonance (NMR) spectroscopy was conducted on (133)Cs(+) in gelatin hydrogels that were either relaxed or stretched. Stretching generated a septet from this spin-7/2 nucleus, and its nuclear magnetic relaxation was studied via z-spectra, and two-dimensional nuclear Overhauser (NOESY) spectroscopy. Various spectral features were well simulated by using Mathematica and the software package SpinDynamica. Spectra of CsCl in suspensions of human erythrocytes embedded in gelatin gel showed separation of the resonances from the cation inside and outside the cells. Upon stretching the sample, the extracellular (133)Cs(+) signal split into a septet, while the intracellular peak was unchanged, revealing different alignment/ordering properties of the environment inside and around the cells. Differential interference contrast light microscopy confirmed that the cells were stretched when the overall sample was elongated. Analysis of the various spectral features of (133)Cs(+) reported here opens up applications of this K(+) congener for studies of cation-handling by metabolically-active cells and tissues in aligned states.