The transient expression of recombinant proteins in plant cell packs facilitates stable isotope labelling for NMR spectroscopy.

Nuclear magnetic resonance (NMR) spectroscopy can be used to determine the structure, dynamics and interactions of proteins. However, protein NMR requires stable isotope labelling for signal detection. The cells used for the production of recombinant proteins must therefore be grown in medium containing isotopically labelled substrates. Stable isotope labelling is well established in Escherichia coli, but bacteria are only suitable for the production of simple proteins without post-translational modifications. More complex proteins require eukaryotic production hosts, but their growth can be impaired by labelled media, thus reducing product yields and increasing costs. To address this limitation, we used media supplemented with isotope-labelled substrates to cultivate the tobacco-derived cell line BY-2, which was then cast into plant cell packs (PCPs) for the transient expression of a labelled version of the model protein GB1. Mass spectrometry confirmed the feasibility of isotope labelling with 15 N and 2 H using this approach. The resulting NMR spectrum featured a signal dispersion comparable to recombinant GB1 produced in E. coli. PCPs therefore offer a rapid and cost-efficient alternative for the production of isotope-labelled proteins for NMR analysis, especially suitable for complex proteins that cannot be produced in microbial systems.

Classification of Polish Natural Bee Honeys Based on Their Chemical Composition.

The targeted quantitative NMR (qNMR) approach is a powerful analytical tool, which can be applied to classify and/or determine the authenticity of honey samples. In our study, this technique was used to determine the chemical profiles of different types of Polish honey samples, featured by variable contents of main sugars, free amino acids, and 5-(hydroxymethyl)furfural. One-way analysis of variance (ANOVA) was performed on concentrations of selected compounds to determine significant differences in their levels between all types of honey. For pattern recognition, principal component analysis (PCA) was conducted and good separations between all honey samples were obtained. The results of present studies allow the differentiation of honey samples based on the content of sucrose, glucose, and fructose, as well as amino acids such as tyrosine, phenylalanine, proline, and alanine. Our results indicated that the combination of qNMR with chemometric analysis may serve as a supplementary tool in specifying honeys.

Rapid Detection of Bacterial and Fungal Pathogens Using the T2MR versus Blood Culture in Patients with Severe COVID-19.

A high rate of bacterial and fungal superinfections was reported in critically ill patients with COVID-19. However, diagnosis can be challenging. The aim of this study is to evaluate the sensitivity and the clinical utility of the point-of-care method T2 magnetic resonance (T2MR) with the gold standard: the blood culture. T2MR can potentially detect five different Candida species and six common bacteria (so-called "ESKAPE" pathogens including Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Acinet`obacter baumanii, Pseudomonas aeruginosa, and Enterococcus faecium). If superinfection was suspected in patients with COVID-19 admitted to the intensive care unit, blood culture and two panels of T2MR were performed. Eighty-five diagnostic bundles were performed in 60 patients in total. T2MR detected an ESKAPE pathogen in 9 out of 85 (10.6%) samples, compared to BC in 3 out of 85 (3.5%). A Candida species was detected in 7 of 85 (8.2%) samples of T2MR compared to 1 out of 85(1.2%) in blood culture. The mean time to positive test result in samples with concordant positive results was 4.5 h with T2MR and 52.5 h with blood culture. The additional use of T2MR enables a highly sensitive and rapid detection of ESKAPE and Candida pathogens. IMPORTANCE Coronavirus disease 2019 (COVID-19) has led to a high number of deaths since the beginning of the pandemic worldwide. One of the reasons is the high number of bacterial and fungal superinfections in patients suffering from critical disease. However, diagnosis is often challenging. In this study we could show that the additional use of the culture-independent method T2MR did not only show a much higher detection rate of bacterial and fungal pathogens but also a significantly shorter time until detection and therapy change compared to the gold standard: the blood culture. The implementation of T2MRin the care of patients with severe course of COVID-19 might lead to an earlier sufficient antimicrobial therapy and as a result lower mortality and less use of broad-spectrum unnecessary therapy reducing the risk of resistance development.

1H NMR Signals from Urine Excreted Protein Are a Source of Bias in Probabilistic Quotient Normalization.

Normalization to account for variation in urinary dilution is crucial for interpretation of urine metabolic profiles. Probabilistic quotient normalization (PQN) is used routinely in metabolomics but is sensitive to systematic variation shared across a large proportion of the spectral profile (>50%). Where 1H nuclear magnetic resonance (NMR) spectroscopy is employed, the presence of urinary protein can elevate the spectral baseline and substantially impact the resulting profile. Using 1H NMR profile measurements of spot urine samples collected from hospitalized COVID-19 patients in the ISARIC 4C study, we determined that PQN coefficients are significantly correlated with observed protein levels (r2 = 0.423, p < 2.2 × 10-16). This correlation was significantly reduced (r2 = 0.163, p < 2.2 × 10-16) when using a computational method for suppression of macromolecular signals known as small molecule enhancement spectroscopy (SMolESY) for proteinic baseline removal prior to PQN. These results highlight proteinuria as a common yet overlooked source of bias in 1H NMR metabolic profiling studies which can be effectively mitigated using SMolESY or other macromolecular signal suppression methods before estimation of normalization coefficients.

Using Unassigned NMR Chemical Shifts to Model RNA Secondary Structure.

NMR-derived chemical shifts are sensitive probes of RNA structure. However, the need to assign NMR spectra hampers their utility as a direct source of structural information. In this report, we describe a simple method that uses unassigned 2D NMR spectra to model the secondary structure of RNAs. As in the case of assigned chemical shifts, we could use unassigned chemical shift data to reweight conformational libraries such that the highest weighted structure closely resembles their reference NMR structure. Furthermore, the application of our approach to the 3'- and 5'-UTR of the SARS-CoV-2 genome yields structures that are, for the most part, consistent with the secondary structure models derived from chemical probing data. Therefore, we expect the framework we describe here will be useful as a general strategy for rapidly generating preliminary structural RNA models directly from unassigned 2D NMR spectra. As we demonstrated for the 337-nt and 472-nt UTRs of SARS-CoV-2, our approach could be especially valuable for modeling the secondary structures of large RNA.

The Extended Hadamard Transform: Sensitivity-Enhanced NMR Experiments Among Labile and Non-Labile 1 Hs of SARS-CoV-2-derived RNAs.

Hadamard encoded saturation transfer can significantly improve the efficiency of NOE-based NMR correlations from labile protons in proteins, glycans and RNAs, increasing the sensitivity of cross-peaks by an order of magnitude and shortening experimental times by ≥100-fold. These schemes, however, fail when tackling correlations within a pool of labile protons - for instance imino-imino correlations in RNAs or amide-amide correlations in proteins. Here we analyze the origin of the artifacts appearing in these experiments and propose a way to obtain artifact-free correlations both within the labile pool as well as between labile and non-labile 1 Hs, while still enjoying the gains arising from Hadamard encoding and solvent repolarizations. The principles required for implementing what we define as the extended Hadamard scheme are derived, and its clean, artifact-free, sensitivity-enhancing performance is demonstrated on RNA fragments derived from the SARS-CoV-2 genome. Sensitivity gains per unit time approaching an order of magnitude are then achieved in both imino-imino and imino-amino/aromatic protons 2D correlations; similar artifact-free sensitivity gains can be observed when carrying out extended Hadamard encodings of 3D NOESY/HSQC-type experiments. The resulting spectra reveal significantly more correlations than their conventionally acquired counterparts, which can support the spectral assignment and secondary structure determination of structured RNA elements.

Structural characterization and SARS-CoV-2 inhibitory activity of a sulfated polysaccharide from Caulerpa lentillifera.

Caulerpa lentillifera (Bryopsidophyceae, Chlorophyta) is an edible seaweed attracting great attention for its expansion of farming scale and increasing consumption in these years. In the present study, a sulfated polysaccharide (CLSP-2) was isolated and separated from C. lentillifera, and its chemical structure was elucidated by a series of chemical and spectroscopic methods. Among these methods, mild acid hydrolysis and photocatalytic degradation were applied to release mono- and oligo-saccharide fragments which were further identified by HPLC-MSn analysis, affording the information of the sugar sequences and the sulfate substitution in CLSP-2. Results indicated that the backbone of CLSP-2 was constructed of →6)-ß-Manp-(1→ with sulfated branches at C2, which were comprised of prevalent →3)-ß-Galp4S-(1→, →3)-ß-Galp2,4S-(1→, and minor Xyl. In addition, the virus neutralization assay revealed that CLSP-2 could effectively protect HeLa cells against SARS-CoV-2 infection with an IC50 of 48.48 µg/mL. Hence, the present study suggests CLSP-2 as a promising agent against SARS-CoV-2.

1H, 13C and 15N resonance assignment of the SARS-CoV-2 full-length nsp1 protein and its mutants reveals its unique secondary structure features in solution.

Structural characterization of the SARS-CoV-2 full length nsp1 protein will be an essential tool for developing new target-directed antiviral drugs against SARS-CoV-2 and for further understanding of intra- and intermolecular interactions of this protein. As a first step in the NMR studies of the protein, we report the 1H, 13C and 15N resonance backbone assignment as well as the Cß of the apo form of the full-lengthSARS-CoV-2 nsp1 including the folded domain together with the flaking N- and C- terminal intrinsically disordered fragments. The 19.8 kD protein was characterized by high-resolution NMR. Validation of assignment have been done by using two different mutants, H81P and K129E/D48E as well as by amino acid specific experiments. According to the obtained assignment, the secondary structure of the folded domain in solution was almost identical to its previously published X-ray structure as well as another published secondary structure obtained by NMR, but some discrepancies have been detected. In the solution SARS-CoV-2 nsp1 exhibited disordered, flexible N- and C-termini with different dynamic characteristics. The short peptide in the beginning of the disordered C-terminal domain adopted two different conformations distinguishable on the NMR time scale. We propose that the disordered and folded nsp1 domains are not fully independent units but are rather involved in intramolecular interactions. Studies of the structure and dynamics of the SARS-CoV-2 mutant in solution are on-going and will provide important insights into the molecular mechanisms underlying these interactions.

Uneven metabolic and lipidomic profiles in recovered COVID-19 patients as investigated by plasma NMR metabolomics.

COVID-19 is a systemic infectious disease that may affect many organs, accompanied by a measurable metabolic dysregulation. The disease is also associated with significant mortality, particularly among the elderly, patients with comorbidities, and solid organ transplant recipients. Yet, the largest segment of the patient population is asymptomatic, and most other patients develop mild to moderate symptoms after SARS-CoV-2 infection. Here, we have used NMR metabolomics to characterize plasma samples from a cohort of the abovementioned group of COVID-19 patients (n = 69), between 3 and 10 months after diagnosis, and compared them with a set of reference samples from individuals never infected by the virus (n = 71). Our results indicate that half of the patient population show abnormal metabolism including porphyrin levels and altered lipoprotein profiles six months after the infection, while the other half show little molecular record of the disease. Remarkably, most of these patients are asymptomatic or mild COVID-19 patients, and we hypothesize that this is due to a metabolic reflection of the immune response stress.

Synthesis, Biological and In Silico Studies of a Tripodal Schiff Base Derived from 2,4,6-Triamino-1,3,5-triazine and Its Trinuclear Dy(III), Er(III), and Gd(III) Salen Capped Complexes.

A tripodal Schiff base ligand, 2,4,6-Tris(4-carboxybenzimino)-1,3,5-triazine (MT) and its trinuclear Dy(III), Er(III), and Gd(III) complexes were synthesized. These were characterized using UV-visible, IR, 1H, and 13C NMR spectroscopies, elemental analysis, and molar conductivity measurements. The spectral studies indicate that the ligand is hexadentate and coordinates to the Ln(III) ions through the oxygen atoms of the carboxylic group. The trinuclear complexes were characterized as being bridged by carboxylate anions to the Dy(III), Er(III), and Gd(III) salen centers and displaying a coordination number of six. Biological studies revealed that MT is more active against the test micro-organisms relative to the trinuclear complexes. Acute toxicity studies revealed that MT is safe and has a wide range of effective doses (ED50). In vivo antimalarial studies indicate that MT could serve as an effective antimalarial agent since it has parasitemia inhibition of 84.02% at 50 mg/kg and 65.81% at 25 mg/kg, close to the value (87.22%) of the standard drug-Artesunate. Molecular docking simulation studies on the compounds against SARS-CoV-2 (6Y84) and E. coli DNA gyrase (5MMN) revealed effective binding interactions through multiple bonding modes. The binding energy calculated for Er(III)MT-6Y84 and Er(III)MT-5MMN complexes showed active molecules with the ability to inhibit SARS-CoV-2 and E. coli DNA gyrase.

Bioactive recombinant human oncostatin M for NMR-based screening in drug discovery.

Oncostatin M (OSM) is a pleiotropic, interleukin-6 family inflammatory cytokine that plays an important role in inflammatory diseases, including inflammatory bowel disease, rheumatoid arthritis, and cancer progression and metastasis. Recently, elevated OSM levels have been found in the serum of COVID-19 patients in intensive care units. Multiple anti-OSM therapeutics have been investigated, but to date no OSM small molecule inhibitors are clinically available. To pursue a high-throughput screening and structure-based drug discovery strategy to design a small molecule inhibitor of OSM, milligram quantities of highly pure, bioactive OSM are required. Here, we developed a reliable protocol to produce highly pure unlabeled and isotope enriched OSM from E. coli for biochemical and NMR studies. High yields (ca. 10 mg/L culture) were obtained in rich and minimal defined media cultures. Purified OSM was characterized by mass spectrometry and circular dichroism. The bioactivity was confirmed by induction of OSM/OSM receptor signaling through STAT3 phosphorylation in human breast cancer cells. Optimized buffer conditions yielded 1H, 15N HSQC NMR spectra with intense, well-dispersed peaks. Titration of 15N OSM with a small molecule inhibitor showed chemical shift perturbations for several key residues with a binding affinity of 12.2 ± 3.9 µM. These results demonstrate the value of bioactive recombinant human OSM for NMR-based small molecule screening.

COVID-19-related cognitive dysfunction may be associated with transient disruption in the DLPFC glutamatergic pathway.

Cognitive impairment has recently attracted researchers as one of the possible neuropsychiatric manifestations of COVID-19, although how the infection perpetuates impairment of cognitive functions is still obscure. We presented a 29-year-old male patient with COVID-19 who developed new-onset transient attention deficit and memory problems following a SARS-CoV-2 infection. Structural neuroimaging was normal. MR-spectroscopy (MRS) of the bilateral DLPFC revealed significant for decreased levels of N-acetylaspartate (NAA), glutamate, and glutamate/glutamine ratio. After a follow-up without any medical treatment but with suggestions of memory exercises for three months a control MRS screening of DLPFC showed improved levels of NAA, glutamate, and glutamate/glutamine ratio. This report may suggest that cognitive deficits in SARS-CoV-2 infection can result from glutamatergic dysfunction with decreased NAA and glutamate levels in bilateral DLPFC.

NMR Spectroscopic Windows on the Systemic Effects of SARS-CoV-2 Infection on Plasma Lipoproteins and Metabolites in Relation to Circulating Cytokines.

To investigate the systemic metabolic effects of SARS-CoV-2 infection, we analyzed 1H NMR spectroscopic data on human blood plasma and co-modeled with multiple plasma cytokines and chemokines (measured in parallel). Thus, 600 MHz 1H solvent-suppressed single-pulse, spin-echo, and 2D J-resolved spectra were collected on plasma recorded from SARS-CoV-2 rRT-PCR-positive patients (n = 15, with multiple sampling timepoints) and age-matched healthy controls (n = 34, confirmed rRT-PCR negative), together with patients with COVID-19/influenza-like clinical symptoms who tested SARS-CoV-2 negative (n = 35). We compared the single-pulse NMR spectral data with in vitro diagnostic research (IVDr) information on quantitative lipoprotein profiles (112 parameters) extracted from the raw 1D NMR data. All NMR methods gave highly significant discrimination of SARS-CoV-2 positive patients from controls and SARS-CoV-2 negative patients with individual NMR methods, giving different diagnostic information windows on disease-induced phenoconversion. Longitudinal trajectory analysis in selected patients indicated that metabolic recovery was incomplete in individuals without detectable virus in the recovery phase. We observed four plasma cytokine clusters that expressed complex differential statistical relationships with multiple lipoproteins and metabolites. These included the following: cluster 1, comprising MIP-1ß, SDF-1α, IL-22, and IL-1α, which correlated with multiple increased LDL and VLDL subfractions; cluster 2, including IL-10 and IL-17A, which was only weakly linked to the lipoprotein profile; cluster 3, which included IL-8 and MCP-1 and were inversely correlated with multiple lipoproteins. IL-18, IL-6, and IFN-γ together with IP-10 and RANTES exhibited strong positive correlations with LDL1-4 subfractions and negative correlations with multiple HDL subfractions. Collectively, these data show a distinct pattern indicative of a multilevel cellular immune response to SARS CoV-2 infection interacting with the plasma lipoproteome giving a strong and characteristic immunometabolic phenotype of the disease. We observed that some patients in the respiratory recovery phase and testing virus-free were still metabolically highly abnormal, which indicates a new role for these technologies in assessing full systemic recovery.

Quantitative In-Vitro Diagnostic NMR Spectroscopy for Lipoprotein and Metabolite Measurements in Plasma and Serum: Recommendations for Analytical Artifact Minimization with Special Reference to COVID-19/SARS-CoV-2 Samples.

Quantitative nuclear magnetic resonance (NMR) spectroscopy of blood plasma is widely used to investigate perturbed metabolic processes in human diseases. The reliability of biochemical data derived from these measurements is dependent on the quality of the sample collection and exact preparation and analysis protocols. Here, we describe systematically, the impact of variations in sample collection and preparation on information recovery from quantitative proton (1H) NMR spectroscopy of human blood plasma and serum. The effects of variation of blood collection tube sizes and preservatives, successive freeze-thaw cycles, sample storage at -80 °C, and short-term storage at 4 and 20 °C on the quantitative lipoprotein and metabolite patterns were investigated. Storage of plasma samples at 4 °C for up to 48 h, freezing at -80 °C and blood sample collection tube choice have few and minor effects on quantitative lipoprotein profiles, and even storage at 4 °C for up to 168 h caused little information loss. In contrast, the impact of heat-treatment (56 °C for 30 min), which has been used for inactivation of SARS-CoV-2 and other viruses, that may be required prior to analytical measurements in low level biosecurity facilities induced marked changes in both lipoprotein and low molecular weight metabolite profiles. It was conclusively demonstrated that this heat inactivation procedure degrades lipoproteins and changes metabolic information in complex ways. Plasma from control individuals and SARS-CoV-2 infected patients are differentially altered resulting in the creation of artifactual pseudo-biomarkers and destruction of real biomarkers to the extent that data from heat-treated samples are largely uninterpretable. We also present several simple blood sample handling recommendations for optimal NMR-based biomarker discovery investigations in SARS CoV-2 studies and general clinical biomarker research.

Secondary structure determination of conserved SARS-CoV-2 RNA elements by NMR spectroscopy.

The current pandemic situation caused by the Betacoronavirus SARS-CoV-2 (SCoV2) highlights the need for coordinated research to combat COVID-19. A particularly important aspect is the development of medication. In addition to viral proteins, structured RNA elements represent a potent alternative as drug targets. The search for drugs that target RNA requires their high-resolution structural characterization. Using nuclear magnetic resonance (NMR) spectroscopy, a worldwide consortium of NMR researchers aims to characterize potential RNA drug targets of SCoV2. Here, we report the characterization of 15 conserved RNA elements located at the 5' end, the ribosomal frameshift segment and the 3'-untranslated region (3'-UTR) of the SCoV2 genome, their large-scale production and NMR-based secondary structure determination. The NMR data are corroborated with secondary structure probing by DMS footprinting experiments. The close agreement of NMR secondary structure determination of isolated RNA elements with DMS footprinting and NMR performed on larger RNA regions shows that the secondary structure elements fold independently. The NMR data reported here provide the basis for NMR investigations of RNA function, RNA interactions with viral and host proteins and screening campaigns to identify potential RNA binders for pharmaceutical intervention.

NMR as a "Gold Standard" Method in Drug Design and Discovery.

Studying disease models at the molecular level is vital for drug development in order to improve treatment and prevent a wide range of human pathologies. Microbial infections are still a major challenge because pathogens rapidly and continually evolve developing drug resistance. Cancer cells also change genetically, and current therapeutic techniques may be (or may become) ineffective in many cases. The pathology of many neurological diseases remains an enigma, and the exact etiology and underlying mechanisms are still largely unknown. Viral infections spread and develop much more quickly than does the corresponding research needed to prevent and combat these infections; the present and most relevant outbreak of SARS-CoV-2, which originated in Wuhan, China, illustrates the critical and immediate need to improve drug design and development techniques. Modern day drug discovery is a time-consuming, expensive process. Each new drug takes in excess of 10 years to develop and costs on average more than a billion US dollars. This demonstrates the need of a complete redesign or novel strategies. Nuclear Magnetic Resonance (NMR) has played a critical role in drug discovery ever since its introduction several decades ago. In just three decades, NMR has become a "gold standard" platform technology in medical and pharmacology studies. In this review, we present the major applications of NMR spectroscopy in medical drug discovery and development. The basic concepts, theories, and applications of the most commonly used NMR techniques are presented. We also summarize the advantages and limitations of the primary NMR methods in drug development.

Polymorphic Forms of Valinomycin Investigated by NMR Crystallography.

A dodecadepsipeptide valinomycin (VLM) has been most recently reported to be a potential anti-coronavirus drug that could be efficiently produced on a large scale. It is thus of importance to study solid-phase forms of VLM in order to be able to ensure its polymorphic purity in drug formulations. The previously available solid-state NMR (SSNMR) data are combined with the plane-wave DFT computations in the NMR crystallography framework. Structural/spectroscopical predictions (the PBE functional/GIPAW method) are obtained to characterize four polymorphs of VLM. Interactions which confer a conformational stability to VLM molecules in these crystalline forms are described in detail. The way how various structural factors affect the values of SSNMR parameters is thoroughly analyzed, and several SSNMR markers of the respective VLM polymorphs are identified. The markers are connected to hydrogen bonding effects upon the corresponding (13C/15N/1H) isotropic chemical shifts of (CO, Namid, Hamid, Hα) VLM backbone nuclei. These results are expected to be crucial for polymorph control of VLM and in probing its interactions in dosage forms.