Nuclear Magnetic Resonance-Based Metabolomic Comparison of Breast Milk and Organic and Traditional Formula Milk Brands for Infants and Toddlers

In recent years, new formula milk (FM) products based on milk from farms that strictly adhere to the "organic farming" practices became available. However, little is known about the differences in nutritional profile of these organic formulae with respect to traditional ones. We comprehensively evaluated the metabolite profiles of FM with nuclear magnetic resonance (NMR)-based metabolomic analysis. Five commercial brands of organic and nonorganic formula liquid milk for infants (0-12 months) and toddlers (1-3 years) were analyzed, together with human milk (HM) samples. Proton NMR (¹H NMR) spectroscopy mapped molecular characteristics of FM linked to different production techniques, and identified differences between FM and HM samples. We performed a metabolic fingerprint analysis using multivariate and univariate statistical techniques. A clear distinction is found among different commercial brands of the FM samples. In addition, several differences in metabolomic profiles of FM have been found in comparison with HM for the first time. Notably, it was possible to identify, both in the formulations for toddlers and for infants, metabolites that vary in concentration between the formulae produced with milk obtained according to organic farming techniques, and those produced using nonorganic milk. In particular, organic and nonorganic formulations are differentiated by the levels of glucose, methionine, o-phosphocholine, butyrate, hippurate, creatine, and dimethyl sulfone. Importantly, the HM appeared to differ from both organic and nonorganic brands in a context of metabolites. These findings inform efforts to design FM in ways that closely mimic HM, and guide research to differentiate organic and traditional FM.

HOPPI-NMR: Hot-Peptide-Based Screening Assay for Inhibitors of Protein-Protein Interactions by NMR

Protein-protein interactions (PPIs) contribute to the onset and/or progression of several diseases, especially cancer, and this discovery has paved the way for considering disruption of the PPIs as an attractive anti-tumor strategy. In this regard, simple and efficient biophysical methods for detecting the interaction of the inhibitors with the protein counterpart are still in high demand. Herein, we describe a convenient NMR method for the screening of putative PPI inhibitors based on the use of "hot peptides" (HOPPI-NMR). As a case study, HOPPI-NMR was successful applied to the well-known p53/MDM2 system. Our outcomes highlight the main advantages of the method, including the use of a small amount of unlabeled proteins, the minimization of the risk of protein aggregation, and the ability to identify weak binders. The last leaves open the possibility for application of HOPPI-NMR in tandem with fragment-based drug discovery as a valid strategy for the identification of novel chemotypes acting as PPI inhibitors.

The Photocatalyzed Thiol-ene reaction: A New Tag to Yield Fast, Selective and reversible Paramagnetic Tagging of Proteins

Paramagnetic restraints have been used in biomolecular NMR for the last three decades to elucidate and refine biomolecular structures, but also to characterize protein-ligand interactions. A common technique to generate such restraints in proteins, which do not naturally contain a (paramagnetic) metal, consists in the attachment to the protein of a lanthanide-binding-tag (LBT). In order to design such LBTs, it is important to consider the efficiency and stability of the conjugation, the geometry of the complex (conformational exchanges and coordination) and the chemical inertness of the ligand. Here we describe a photo-catalyzed thiol-ene reaction for the cysteine-selective paramagnetic tagging of proteins. As a model, we designed an LBT with a vinyl-pyridine moiety which was used to attach our tag to the protein GB1 in fast and irreversible fashion. Our tag T1 yields magnetic susceptibility tensors of significant size with different lanthanides and has been characterized using NMR and relaxometry measurements.

Fingerprinting Alzheimer's Disease by 1H Nuclear Magnetic Resonance Spectroscopy of Cerebrospinal Fluid

In this study, we sought for a cerebrospinal fluid (CSF) metabolomic fingerprint in Alzheimer's disease (AD) patients characterized, according to the clinical picture and CSF AD core biomarkers (Aβ₄₂, p-tau, and t-tau), both at pre-dementia (mild cognitive impairment due to AD, MCI-AD) and dementia stages (ADdem) and in a group of patients with a normal CSF biomarker profile (non-AD) using untargeted ¹H nuclear magnetic resonance (NMR) spectroscopy-based metabolomics. This is a retrospective study based on two independent cohorts: a Dutch cohort, which comprises 20 ADdem, 20 MCI-AD, and 20 non-AD patients, and an Italian cohort, constituted by 14 ADdem and 12 non-AD patients. ¹H NMR CSF spectra were analyzed using OPLS-DA. Metabolomic fingerprinting in the Dutch cohort provides a significant discrimination (86.1% accuracy) between ADdem and non-AD. MCI-AD patients show a good discrimination with respect to ADdem (70.0% accuracy) but only slight differences when compared with non-AD (59.6% accuracy). Acetate, valine, and 3-hydroxyisovalerate result to be altered in ADdem patients. Valine correlates with cognitive decline at follow-up (R = 0.53, P = 0.0011). The discrimination between ADdem and non-AD was confirmed in the Italian cohort. The CSF metabolomic fingerprinting shows a signature characteristic of ADdem patients with respect to MCI-AD and non-AD patients.

Multivariate Curve Resolution for 2D Solid-State NMR spectra

We present a processing method, based on the multivariate curve resolution approach (MCR), to denoise 2D solid-state NMR spectra, yielding a substantial S/N ratio increase while preserving the lineshapes and relative signal intensities. These spectral features are particularly important in the quantification of silicon species, where sensitivity is limited by the low natural abundance of the ²⁹Si nuclei and by the dilution of the intrinsic protons of silica, but can be of interest also when dealing with other intermediate-to-low receptivity nuclei. This method also offers the possibility of coprocessing multiple 2D spectra that have the signals at the same frequencies but with different intensities (e.g.: as a result of a variation in the mixing time). The processing can be carried out on the time-domain data, thus preserving the possibility of applying further processing to the data. As a demonstration, we have applied Cadzow denoising on the MCR-processed FIDs, achieving a further increase in the S/N ratio and more effective denoising also on the transients at longer indirect evolution times. We have applied the combined denoising on a set of experimental data from a lysozyme-silica composite.

Differential Network Analysis Reveals Metabolic Determinants Associated with Mortality in Acute Myocardial Infarction Patients and Suggests Potential Mechanisms Underlying Different Clinical Scores Used To Predict Death

We present here the differential analysis of metabolite–metabolite association networks constructed from an array of 24 serum metabolites identified and quantified via nuclear magnetic resonance spectroscopy in a cohort of 825 patients of which 123 died within 2 years from acute myocardial infarction (AMI). We investigated differences in metabolite connectivity of patients who survived, at 2 years, the AMI event, and we characterized metabolite–metabolite association networks specific to high and low risks of death according to four different risk parameters, namely, acute coronary syndrome classification, Killip, Global Registry of Acute Coronary Events risk score, and metabolomics NOESY RF risk score. We show significant differences in the connectivity patterns of several low-molecular-weight molecules, implying variations in the regulation of several metabolic pathways regarding branched-chain amino acids, alanine, creatinine, mannose, ketone bodies, and energetic metabolism. Our results demonstrate that the characterization of metabolite–metabolite association networks is a promising and powerful tool to investigate AMI patients according to their outcomes at a molecular level.

On the complementarity of X-ray and NMR data

X-ray crystallography and NMR contain complementary information for the structural characterization of biological macromolecules. X-ray diffraction is primarily sensitive to the overall shape of the molecule, whereas NMR is mostly sensitive to the atomic detail. Their combination can therefore provide a stronger justification for the resulting structure. For their combination we have recently proposed REFMAC-NMR, which relies on primary data from both techniques for joint refinement. This possibility raises the compelling question of how far the complementarity can be extended. In this paper, we describe an integrative approach to the refinement with NMR data of four X-ray structures of hen-egg-white lysozyme, solved at atomic resolution in four different crystal forms, and we demonstrate that the outcome critically depends on the crystal form itself, reflecting the sensitivity of NMR to fine details.

Mixing Aβ(1–40) and Aβ(1–42) peptides generates unique amyloid fibrils

Solid-state NMR experiments reveal that the two isoforms of the beta-amyloid peptide (Aβ(1–40) and Aβ(1–42)) are able to form unique interlaced mixed fibrils.

NMR of Immobilized Enzymes

Solid-state NMR has become the method of choice for the assessment of protein structure for insoluble objects lacking long-range order. In this context, it is apparent that solid-state NMR is also perfectly poised toward the characterization of immobilized proteins. For these systems, it is possible to understand at the atomic level which perturbations, if any, are occurring as a result of the functionalization. Here we describe how it is possible to accomplish the NMR characterization of enzymes that have been immobilized through different approaches, and we introduce the reader to the choice of the experimental strategy that can be useful in different cases. An outlook on the level of information that can be attained is also given, in view of recent methodological advancements.

A protocol to automatically calculate homo-oligomeric protein structures through the integration of evolutionary constraints and NMR ambiguous contacts

Protein assemblies are involved in many important biological processes. Solid-state NMR (SSNMR) spectroscopy is a technique suitable for the structural characterization of samples with high molecular weight and thus can be applied to such assemblies. A significant bottleneck in terms of both effort and time required is the manual identification of unambiguous intermolecular contacts. This is particularly challenging for homo-oligomeric complexes, where simple uniform labeling may not be effective. We tackled this challenge by exploiting coevolution analysis to extract information on homo-oligomeric interfaces from NMR-derived ambiguous contacts. After removing the evolutionary couplings (ECs) that are already satisfied by the 3D structure of the monomer, the predicted ECs are matched with the automatically generated list of experimental contacts. This approach provides a selection of potential interface residues that is used directly in monomer-monomer docking calculations. We validated the protocol on tetrameric L-asparaginase II and dimeric Sod1.

The inner temperature of the olives (cv. Leccino) before processing affects the volatile profile and the composition of the oil

The effects of pre-processing decreasing temperature (19, 15 and 10 °C) of olive fruit (cv. Leccino) harvested at three developmental stages (semi-ripe, ripe, advanced ripening) have been evaluated on oil in terms of basic quality parameters, composition, organoleptic traits, and aroma profiles. A total of 40 metabolites (volatiles and non-volatiles) were identified by ¹H NMR and GC/MS analyses. Multivariate statistical analysis showed that samples obtained from ripe and advanced ripe olives cooled at 10 and 15 °C better correlated with C6 aldehydes, mainly associated with herbal/green olfactory traits. Compounds responsible for sweet/fruity traits were more abundantly present in oil extracted from 19 °C olive samples. Decreasing pulp temperature before crushing also resulted in reduced presence of 1-penten-3-ol, 1-penten-3-one, acetic acid and ethyl alcohol, associated with specific defects of the oil. Results indicate that slightly lowering fruit temperature just before crushing modulates oil composition by reducing oil off flavours while enhancing green and fresh attributes in particular when ripe olives are processed.

Insights into telomeric G-quadruplex DNA recognition by HMGB1 protein

HMGB1 is a ubiquitous non-histone protein, which biological effects depend on its expression and subcellular location. Inside the nucleus, HMGB1 is engaged in many DNA events such as DNA repair, transcription and telomere maintenance. HMGB1 has been reported to bind preferentially to bent DNA as well as to noncanonical DNA structures like 4-way junctions and, more recently, to G-quadruplexes. These are four-stranded conformations of nucleic acids involved in important cellular processes, including telomere maintenance. In this frame, G-quadruplex recognition by specific proteins represents a key event to modulate physiological or pathological pathways. Herein, to get insights into the telomeric G-quadruplex DNA recognition by HMGB1, we performed detailed biophysical studies complemented with biological analyses. The obtained results provided information about the molecular determinants for the interaction and showed that the structural variability of human telomeric G-quadruplex DNA may have significant implications in HMGB1 recognition. The biological data identified HMGB1 as a telomere-associated protein in both telomerase-positive and -negative tumor cells and showed that HMGB1 gene silencing in such cells induces telomere DNA damage foci. Altogether, these findings provide a deeper understanding of telomeric G-quadruplex recognition by HMGB1 and suggest that this protein could actually represent a new target for cancer therapy.

Assessing Structural Preferences of Unstructured Protein Regions by NMR

Biomacromolecules, such as proteins, often exhibit significant motions intimately associated with their function. Intrinsically disordered proteins and proteins with intrinsically disordered regions, although extremely important for a plethora of cellular functions, are difficult to structurally characterize at the atomic level because the experimental parameters report on ensemble and time averages. Here, we demonstrate for the C-terminal domain of the human immunodeficiency virus type 1 capsid protein that NMR and, in particular, residual dipolar couplings (RDCs) measured for the folded portion of the protein can inform on the structural preferences of the unstructured portion using RDC-prediction tools and the maximum occurrence approach.

NMR-Based Metabolomics for the Assessment of Inhaled Pharmacotherapy in Chronic Obstructive Pulmonary Disease Patients

The aim of this proof-of-concept, pilot study was the evaluation of the effects of steroid administration and suspension of an inhaled corticosteroid (ICS)-long-acting β₂-agonist (LABA) extrafine fixed dose combination (FDC) on metabolomic fingerprints in subjects with chronic obstructive pulmonary disease (COPD). We hypothesized that a comprehensive metabolomics approach discriminates across inhaled pharmacotherapies and that their effects on metabolomic signatures depend on the biological fluids analyzed. We performed metabolomics via nuclear magnetic resonance (NMR) spectroscopy in exhaled breath condensate (EBC), sputum supernatants, serum, and urine. Fourteen patients suffering from COPD who were on regular inhaled fluticasone propionate/salmeterol therapy (visit 1) were consecutively treated with 2-week beclomethasone dipropionate/formoterol (visit 2), 4-week formoterol alone (visit 3), and 4-week beclomethasone/formoterol (visit 4). The comprehensive NMR-based metabolomics approach showed differences across all pharmacotherapies and that different biofluids provided orthogonal information. Serum formate was lower at visits 1 versus 3 (P = 0.03), EBC formate was higher at visit 1 versus 4 (P = 0.03), and urinary 1-methyl-nicotinamide was lower at 3 versus 4 visit (P = 0.002). NMR-based metabolomics of different biofluids distinguishes across inhaled pharmacotherapies, provides complementary information on the effects of an extrafine ICS/LABA FDC on metabolic fingerprints in COPD patients, and might be useful for elucidating the ICS mechanism of action.

Magnetic susceptibility and paramagnetism-based NMR

The magnetic interactions between the nuclear magnetic moment and the magnetic moment of unpaired electron(s) depend on the structure and dynamics of the molecules where the paramagnetic center is located and of their partners. The long-range nature of the magnetic interactions is thus a reporter of invaluable information for structural biology studies, when other techniques often do not provide enough data for the atomic-level characterization of the system. This precious information explains the flourishing of paramagnetism-assisted NMR studies in recent years. Many paramagnetic effects are related to the magnetic susceptibility of the paramagnetic metal. Although these effects have been known for more than half a century, different theoretical models and new approaches have been proposed in the last decade. In this review, we have summarized the consequences for NMR spectroscopy of magnetic interactions between nuclear and electron magnetic moments, and thus of the presence of a magnetic susceptibility due to metals, and we do so using a unified notation.

Mechanism and Inhibition of Matrix Metalloproteinases

Matrix metalloproteinases hydrolyze proteins and glycoproteins forming the extracellular matrix, cytokines and growth factors released in the extracellular space, and membrane-bound receptors on the outer cell membrane. The pathological relevance of MMPs has prompted the structural and functional characterization of these enzymes and the development of synthetic inhibitors as possible drug candidates. Recent studies have provided a better understanding of the substrate preference of the different members of the family, and structural data on the mechanism by which these enzymes hydrolyze the substrates. Here, we report the recent advancements in the understanding of the mechanism of collagenolysis and elastolysis, and we discuss the perspectives of new therapeutic strategies for targeting MMPs.

What are the methodological and theoretical prospects for paramagnetic NMR in structural biology? A glimpse into the crystal ball

NMR spectroscopy is very sensitive to the presence of unpaired electrons, which perturb the NMR chemical shifts, J splittings and nuclear relaxation rates. These paramagnetic effects have attracted increasing attention over the last decades, and their use is expected to increase further in the future because they can provide structural information not easily achievable with other techniques. In fact, paramagnetic data provide long range structural restraints that can be used to assess the accuracy of crystal structures in solution and to improve them by simultaneous refinements with the X-ray data. They are also precious for obtaining information on the conformational variability of biomolecular systems, possibly in conjunction with SAXS and/or DEER data. We foresee that new tools will be developed in the next years for the simultaneous analysis of the paramagnetic data with data obtained from different techniques, in order to take advantage synergistically of the information content of all of them. Of course, the use of the paramagnetic data for structural purposes requires the knowledge of the relationship between these data and the molecular coordinates. Recently, the equations commonly used, dating back to half a century ago, have been questioned by first principle quantum chemistry calculations. Our prediction is that further theoretical/computational improvements will essentially confirm the validity of the old semi-empirical equations for the analysis of the experimental paramagnetic data.

Metabolomic analysis of serum may refine 21-gene expression assay risk recurrence stratification

Despite recent refinements to the 21-gene g score, allowing a better identification of patients who may derive no benefit from the addition of adjuvant chemotherapy to that of endocrine therapy, patients with early breast cancer still stand to be over-treated in the setting of clinical and/or genomic uncertainty or discordance. Here we describe and demonstrate a potential approach of further refining the OncotypeDX risk score by metabolomic analysis of serum. In a clinical dataset (N = 87), the risk of recurrence was further sub-stratified by metabolomic signature, with an effective splitting of each Oncotype risk classification. A total of seven recurrences were recorded, with metabolomic analysis accurately predicting six of these. Contrastingly, the genomic risk score of the seven recurrences ranged across all three Oncotype classifications (one recurrence occurred in the "low"-risk group, three in the "intermediate" group and three in the "high"-risk group).

Relaxivity of Gd-Based MRI Contrast Agents in Crosslinked Hyaluronic Acid as a Model for Tissues

The efficiency of MRI contrast agents depends on the relaxation rate enhancement that they can induce at imaging fields. It is well known that, at these fields, large relaxation rates are obtained by binding of gadolinium(III) ions to large molecules. By the same token, the interaction of the gadolinium(III) complexes with macromolecules that are found in biological tissues can be responsible for an increase of the relaxation rate with respect to the value observed in liquids. We investigate here the relaxation enhancement of gadoteridol (Gd-HP-DO3A) in crosslinked hyaluronic acid, taken as model tissue, using fast field-cycling relaxometry. The analysis of the relaxation profiles as a function of the magnetic fields indicates that a sizable increase in the relaxation rates is due to a modest interaction of the contrast agent with the hydrogel and to the slower mobility of the water molecules outside the first-coordination sphere of the gadolinium(III) ion.

Nanoparticles for the multivalent presentation of a TnThr mimetic and as tool for solid state NMR coating investigation

The fully characterization of tumor associated antigens (TAAs) and of tumor associated carbohydrate antigens (TACAs) have opened the avenue of cancer immunotherapy. The intrinsic poor immunogenicity of TACAs, however, spotlighted the importance of multivalent presentation of the antigen(s) to trigger an immune response. Nanoparticles are excellent scaffolds for this purpose. Here we reported on the easy glycosylation of iron-based and biocompatible dextran-based nanoparticles with 1, a mimetic of the TnThr antigen. The multivalent presentation of 1 induced the induction of TNF-α and IL-6/IL10, respectively. The multivalent glycosylation of silica nanoparticles (GSiNPs) was also performed and saccharide loading qualitative assessed by solid state NMR. Our results offer the proof of concept that biomolecules coating can also be investigated on solid system by NMR.

How Do Nuclei Couple to the Magnetic Moment of a Paramagnetic Center? A New Theory at the Gauntlet of the Experiments

The recent derivation, based on pure quantum chemistry (QC) first-principles, of the pseudocontact shifts (PCSs) caused by a paramagnetic metal center on far away nuclei has cast doubts on the validity of the semiempirical (SE) theory, predicting PCSs to arise from the metal magnetic susceptibility anisotropy. The SE theory has been used and applied countless times, especially in the last 2 decades, to obtain structural information on proteins containing paramagnetic metal ions. We show here that the QC and SE predictions can be directly tested against experiments, provided a suitable macromolecular system is used. The SE approach yields a good prediction of the experimental PCSs while the QC one does not. It appears that the classic theory is able to grasp satisfactorily the underlying physics.