Correction to: Joint X-ray/NMR structure refinement of multidomain/multisubunit systems

The article "Joint X-ray/NMR structure refinement of multidomain/multisubunit systems" written by "Azzurra Carlon, Enrico Ravera, Giacomo Parigi, Garib N. Murshudov and Claudio Luchinat" was originally published electronically on the publisher's internet portal (currently SpringerLink) on 11 October 2018 without open access.

Joint X-ray/NMR structure refinement of multidomain/multisubunit systems

Data integration in structural biology has become a paradigm for the characterization of biomolecular systems, and it is now accepted that combining different techniques can fill the gaps in each other's blind spots. In this frame, one of the combinations, which we have implemented in REFMAC-NMR, is residual dipolar couplings from NMR together with experimental data from X-ray diffraction. The first are exquisitely sensitive to the local details but does not give any information about overall shape, whereas the latter encodes more the information about the overall shape but at the same time tends to miss the local details even at the highest resolutions. Once crystals are obtained, it is often rather easy to obtain a complete X-ray dataset, however it is time-consuming to obtain an exhaustive NMR dataset. Here, we discuss the effect of including a-priori knowledge on the properties of the system to reduce the number of experimental data needed to obtain a more complete picture. We thus introduce a set of new features of REFMAC-NMR that allow for improved handling of RDC data for multidomain proteins and multisubunit biomolecular complexes, and encompasses the use of pseudo-contact shifts as an additional source of NMR-based information. The new feature may either help in improving the refinement, or assist in spotting differences between the crystal and the solution data. We show three different examples where NMR and X-ray data can be reconciled to a unique structural model without invoking mobility.

Structural characterization of a protein adsorbed on aluminum hydroxide adjuvant in vaccine formulation

The heterogeneous composition of vaccine formulations and the relatively low concentration make the characterization of the protein antigens extremely challenging. Aluminum-containing adjuvants have been used to enhance the immune response of several antigens over the last 90 years and still remain the most commonly used. Here, we show that solid-state NMR and isotope labeling methods can be used to characterize the structural features of the protein antigen component of vaccines and to investigate the preservation of the folding state of proteins adsorbed on Alum hydroxide matrix, providing the way to identify the regions of the protein that are mainly affected by the presence of the inorganic matrix. l-Asparaginase from E. coli has been used as a pilot model of protein antigen. This methodology can find application in several steps of the vaccine development pipeline, from the antigen optimization, through the design of vaccine formulation, up to stability studies and manufacturing process.

Dissecting the Interactions between Human Serum Albumin and α-Synuclein: New Insights on the Factors Influencing α-Synuclein Aggregation in Biological Fluids

α-Synuclein (α-syn) is found to be naturally present in biofluids such as cerebrospinal fluid (CSF) and serum. Human serum albumin (HSA) is the most abundant protein found in these biofluids, which, beyond transporting hormones and drugs, also exerts a chaperone-like activity binding other proteins in blood and inhibiting their aggregation. Contrasting results are reported in the literature about the effects of albumin on α-syn aggregation. We characterized the binding region of HSA on α-syn by high-field solution NMR spectroscopy and the effect of HSA on α-syn aggregation by thioflavin-T (ThT) fluorescence under both low-ionic-strength and physiological conditions at the albumin concentration in serum and CSF. We found that HSA, at the concentration found in human serum, slows the aggregation of α-syn significantly. α-Syn interacts with HSA in an ionic strength- and pH-dependent manner. The binding is driven by hydrophobic interactions at the N-terminus under physiological experimental conditions and by electrostatic interactions at the C-terminus at low ionic strength. This work provides novel information about the proteostasis of α-syn in biofluids and supports the hypothesis of a chaperone-like behavior of HSA.

NMR for sample quality assessment in metabolomics

The EU Framework 7 project SPIDIA was the occasion for development of NMR approaches to evaluate the impact of different pre-analytical treatments on the quality of biological samples dedicated to metabolomics. Systematic simulation of different pre-analytical procedures was performed on urine and blood serum and plasma. Here we review the key aspects of these studies that have led to the development of CEN technical specifications, to be translated into ISO/IS in the course of the EU Horizon 2020 project SPIDIA4P. Inspired by the SPIDIA results, follow-up research was performed, extending the analysis to different sample types and to the different effects of long-term storage. The latter activity was in conjunction with the local European da Vinci Biobank. These results (which partially contributed to the ANNEX of CEN/TS 16945"MOLECULAR IN VITRO DIAGNOSTIC EXAMINATIONS - SPECIFICATIONS FOR PRE-EXAMINATION PROCESSES FOR METABOLOMICS IN URINE, VENOUS BLOOD SERUM AND PLASMA") are presented in detail.

Bimodal Fluorescence-Magnetic Resonance Contrast Agent for Apoptosis Imaging

Effective cancer therapy largely depends on inducing apoptosis in cancer cells via chemotherapy and/or radiation. Monitoring apoptosis in real-time provides invaluable information for evaluating cancer therapy response and screening preclinical anticancer drugs. In this work, we describe the design, synthesis, characterization, and in vitro evaluation of caspase probe 1 (CP1), a bimodal fluorescence-magnetic resonance (FL-MR) probe that exhibits simultaneous FL-MR turn-on response to caspase-3/7. Both caspases exist as inactive zymogens in normal cells but are activated during apoptosis and are unique biomarkers for this process. CP1 has three distinct components: a DOTA-Gd(III) chelate that provides the MR signal enhancement, tetraphenylethylene as the aggregation induced emission luminogen (AIEgen), and DEVD peptide which is a substrate for caspase-3/7. In response to caspase-3/7, the water-soluble peptide DEVD is cleaved and the remaining Gd(III)-AIEgen (Gad-AIE) conjugate aggregates leading to increased FL-MR signals. CP1 exhibited sensitive and selective dual FL-MR turn-on response to caspase-3/7 in vitro and was successfully tested by fluorescence imaging of apoptotic cells. Remarkably, we were able to use the FL response of CP1 to quantify the exact concentrations of inactive and active agents and accurately predict the MR signal in vitro. We have demonstrated that the aggregation-driven FL-MR probe design is a unique method for MR signal quantification. This probe design platform can be adapted for a variety of different imaging targets, opening new and exciting avenues for multimodal molecular imaging.

Pseudocontact shifts and paramagnetic susceptibility in semiempirical and quantum chemistry theories

Pseudocontact shifts are traditionally described as a function of the anisotropy of the paramagnetic susceptibility tensor, according to the semiempirical theory mainly developed by Kurland and McGarvey [J. Magn. Reson. 2, 286-301 (1970)]. The paramagnetic susceptibility tensor is required to be symmetric. Applying point-dipole approximation to the quantum chemistry theory of hyperfine shift, pseudocontact shifts are found to scale with a non-symmetric tensor that differs by a factor g^T/g_e from the paramagnetic susceptibility tensor derived within the semiempirical framework. We analyze the foundations of the Kurland-McGarvey pseudocontact shift expression and recall that it is inherently based on the Russell-Saunders (LS) coupling approximation for the spin-orbit coupling. We show that the difference between the semiempirical and quantum chemistry pseudocontact shift expressions arises directly from the different treatment of the orbital contribution to the hyperfine coupling.

The metabolic fingerprints of HCV and HBV infections studied by Nuclear Magnetic Resonance Spectroscopy

Few studies are available on metabolic changes in liver injuries and this is the first metabolomic study evaluating a group of HCV-positive patients, before and after viral eradication via DAA IFN-free regimens, using ¹H-NMR to characterize and compare their serum fingerprints to naïve HBV-patients and healthy donors. The investigation clearly shows differences in the metabolomic profile of HCV patients before and after effective DAA treatment. Significant changes in metabolites levels in patients undergoing therapy suggest alterations in several metabolic pathways. It has been shown that ¹H-NMR fingerprinting approach is an optimal technique in predicting the specific infection and the healthy status of studied subjects (Monte-Carlo cross validated accuracies: 86% in the HCV vs HBV model, 98.7% in the HCV vs HC model). Metabolite data collected support the hypothesis that the HCV virus induces glycolysis over oxidative phosphorylation in a similar manner to the Warburg effect in cancer, moreover our results have demonstrated a different action of the two viruses on cellular metabolism, corroborating the hypothesis that the metabolic perturbation on patients could be attributed to a direct role in viral infection. This metabolomic study has revealed some alteration in metabolites for the first time (2-oxoglutarate and 3-hydroxybutrate) concerning the HCV-infection model that could explain several extrahepatic manifestations associated with such an infection.

High-Throughput Metabolomics by 1D NMR

Metabolomics deals with the whole ensemble of metabolites (the metabolome). As one of the -omic sciences, it relates to biology, physiology, pathology and medicine; but metabolites are chemical entities, small organic molecules or inorganic ions. Therefore, their proper identification and quantitation in complex biological matrices requires a solid chemical ground. With respect to for example, DNA, metabolites are much more prone to oxidation or enzymatic degradation: we can reconstruct large parts of a mammoth's genome from a small specimen, but we are unable to do the same with its metabolome, which was probably largely degraded a few hours after the animal's death. Thus, we need standard operating procedures, good chemical skills in sample preparation for storage and subsequent analysis, accurate analytical procedures, a broad knowledge of chemometrics and advanced statistical tools, and a good knowledge of at least one of the two metabolomic techniques, MS or NMR. All these skills are traditionally cultivated by chemists. Here we focus on metabolomics from the chemical standpoint and restrict ourselves to NMR. From the analytical point of view, NMR has pros and cons but does provide a peculiar holistic perspective that may speak for its future adoption as a population-wide health screening technique.

Metabolic Signature of Primary Biliary Cholangitis and Its Comparison with Celiac Disease

Primary biliary cholangitis (PBC) is a chronic autoimmune liver disease characterized by ongoing inflammatory destruction of the interlobular bile ducts, eventually leading to chronic cholestasis and biliary cirrhosis. This study primarily aims to define the metabolomic signature of PBC after comparison with healthy controls (HC). Second, it aims to evaluate the possible metabolic association between PBC and celiac disease (CD), an immune-mediated disorder frequently associated with PBC. Serum and urine samples from 20 PBC, 21 CD, and 19 sex-matched HC subjects were collected. ¹H nuclear magnetic resonance (NMR) spectra for all samples were acquired, and multivariate statistics were used to evaluate the differences among the three groups and to provide information about the involved metabolites. The classification accuracies to discriminate PBC and HC groups were 78.9-84.6% for serum and 76.9% for urine. In comparison to HC, PBC patient sera were characterized by altered levels ( p value <0.05) of pyruvate, citrate, glutamate, glutamine, serine, tyrosine, phenylalanine, and lactate. PBC patient urine showed lower levels ( p value <0.05) of trigonelline and hippurate with respect to HC. Furthermore, the NMR metabolomic fingerprint was able to cluster PBC with respect to CD patients, and the classification accuracies in the discriminations between these groups were 81.9-91.7% for serum and 77.7% for urine. Our results show that PBC displays a unique metabolomic fingerprint, which led to speculation about an impaired energy metabolism, probably associated with an altered gut microbiota. PBC and CD showed two distinct metabolic fingerprints. These data could provide clues for the comprehension of the PBC pathogenetic mechanisms and the detection of novel therapeutic targets.

NMR-based metabolomics identifies patients at high risk of death within two years after acute myocardial infarction in the AMI-Florence II cohort

BACKGROUND

Risk stratification and management of acute myocardial infarction patients continue to be challenging despite considerable efforts made in the last decades by many clinicians and researchers. The aim of this study was to investigate the metabolomic fingerprint of acute myocardial infarction using nuclear magnetic resonance spectroscopy on patient serum samples and to evaluate the possible role of metabolomics in the prognostic stratification of acute myocardial infarction patients.

METHODS

In total, 978 acute myocardial infarction patients were enrolled in this study; of these, 146 died and 832 survived during 2 years of follow-up after the acute myocardial infarction. Serum samples were analyzed via high-resolution ¹H-nuclear magnetic resonance spectroscopy and the spectra were used to characterize the metabolic fingerprint of patients. Multivariate statistics were used to create a prognostic model for the prediction of death within 2 years after the cardiovascular event.

RESULTS

In the training set, metabolomics showed significant differential clustering of the two outcomes cohorts. A prognostic risk model predicted death with 76.9% sensitivity, 79.5% specificity, and 78.2% accuracy, and an area under the receiver operating characteristics curve of 0.859. These results were reproduced in the validation set, obtaining 72.6% sensitivity, 72.6% specificity, and 72.6% accuracy. Cox models were used to compare the known prognostic factors (for example, Global Registry of Acute Coronary Events score, age, sex, Killip class) with the metabolomic random forest risk score. In the univariate analysis, many prognostic factors were statistically associated with the outcomes; among them, the random forest score calculated from the nuclear magnetic resonance data showed a statistically relevant hazard ratio of 6.45 (p = 2.16×10^-16). Moreover, in the multivariate regression only age, dyslipidemia, previous cerebrovascular disease, Killip class, and random forest score remained statistically significant, demonstrating their independence from the other variables.

CONCLUSIONS

For the first time, metabolomic profiling technologies were used to discriminate between patients with different outcomes after an acute myocardial infarction. These technologies seem to be a valid and accurate addition to standard stratification based on clinical and biohumoral parameters.

Assessing protein conformational landscapes: integration of DEER data in Maximum Occurrence analysis

The properties of the conformational landscape of a biomolecule are of capital importance to understand its function. It is widely accepted that a statistical ensemble is far more representative than a single structure, especially for proteins with disordered regions. While experimental data provide the most important handle on the conformational variability that the system is experiencing, they usually report on either time or ensemble averages. Since the available conformations largely outnumber the (independent) available experimental data, the latter can be equally well reproduced by a variety of ensembles. We have proposed the Maximum Occurrence (MaxOcc) approach to provide an upper bound of the statistical weight of each conformation. This method is expected to converge towards the true statistical weights by increasing the number of independent experimental datasets. In this paper we explore the ability of DEER (Double Electron Electron Resonance) data, which report on the distance distribution between two spin labels attached to a biomolecule, to restrain the MaxOcc values and its complementarity to previously introduced experimental techniques such as NMR and Small-Angle X-ray Scattering. We here present the case of Ca2+ bound calmodulin (CaM) as a test case and show that DEER data impose a sizeable reduction of the conformational space described by high MaxOcc conformations.

Protein Glycosylation through Sulfur Fluoride Exchange (SuFEx) Chemistry: The Key Role of a Fluorosulfate Thiolactoside

Protein glycosylation is the most complex post-translational modification process. More than 50 % of human cells proteins are glycosylated, whereas bacteria such as E. coli do not have this modification machinery. Indeed, the carbohydrate residues in natural proteins affect their folding, immunogenicity, and stability toward proteases, besides controlling biological properties and activities. It is therefore important to introduce such structural modification in bioengineered proteins lacking the presence of carbohydrate residues. This is not trivial as it requires reagents and conditions compatible with the protein's stability and reactivity. This work reports on the introduction of lactose moieties in two natural proteins, namely ubiquitin (Ub) and l-asparaginase II (ANSII). The synthetic route employed is based on the sulfur(VI) fluoride exchange (SuFEx) coupling of a lactose tethered arylfluorosulfate (Lact-Ar-OSO₂ F) with the ϵ-NH₂ group of lysine residues of the proteins. This metal-free click SuFEx reaction relies on the properties of the fluorosulfate employed, which is easily prepared in multigram scale from available precursors and reacts chemoselectively with the ϵ-NH₂ group of lysine residues under mild conditions. Thus, iterative couplings of Lact-Ar-OSO₂ F to Ub and ANSII, afforded multiple glycosylations of these proteins so that up to three and four Lact-Ar-OSO₂ groups were introduced in Ub and ANSII, respectively, via the formation of a sulfamoyl (OSO₂ -NH) linkage.

Non-crystallographic symmetry in proteins: Jahn-Teller-like and Butterfly-like effects?

Partial symmetry, i.e., the presence of more than one molecule in the asymmetric unit of a crystal, is a relatively rare phenomenon in small-molecule crystallography, but is quite common in protein crystallography, where it is typically known as non-crystallographic symmetry (NCS). Several papers in literature propose molecular determinants such as crystal contacts, thermal factors, or TLS parameters as an explanation for the phenomenon of intrinsic asymmetry among molecules that are in principle equivalent. Nevertheless, are all of the above determinants the cause or are they rather the effect? In the general frame of the NCS often observed in crystals of biomolecules, this paper deals with nickel(II)-substituted human carbonic anhydrase(II) (hCAII) and its SAD structure determination at the nickel edge. The structure revealed two non-equivalent molecules in the asymmetric unit, the presence of a secondary nickel-binding site at the N-terminus of both molecules (which had never been found before in the nickel-substituted enzyme) and two different coordination geometries of the active site nickel (hexa-coordinated in one molecule and mainly penta-coordinated in the other). The above-mentioned standard molecular crystallographic determinants of this asymmetry are analyzed and presented in detail for this particular case. From these considerations, we speculate on the existence of a fundamental, although yet unknown, common cause for the partial symmetry that is so often encountered in X-ray structures of biomolecules.

Fingerprinting Acute Digestive Diseases by Untargeted NMR Based Metabolomics

Precision medicine may significantly contribute to rapid disease diagnosis and targeted therapy, but relies on the availability of detailed, subject specific, clinical information. Proton nuclear magnetic resonance (¹H–NMR) spectroscopy of body fluids can extract individual metabolic fingerprints. Herein, we studied 64 patients admitted to the Florence main hospital emergency room with severe abdominal pain. A blood sample was drawn from each patient at admission, and the corresponding sera underwent ¹H–NMR metabolomics fingerprinting. Unsupervised Principal Component Analysis (PCA) analysis showed a significant discrimination between a group of patients with symptoms of upper abdominal pain and a second group consisting of patients with diffuse abdominal/intestinal pain. Prompted by this observation, supervised statistical analysis (Orthogonal Partial Least Squares–Discriminant Analysis (OPLS-DA)) showed a very good discrimination (>90%) between the two groups of symptoms. This is a surprising finding, given that neither of the two symptoms points directly to a specific disease among those studied here. Actually herein, upper abdominal pain may result from either symptomatic gallstones, cholecystitis, or pancreatitis, while diffuse abdominal/intestinal pain may result from either intestinal ischemia, strangulated obstruction, or mechanical obstruction. Although limited by the small number of samples from each of these six conditions, discrimination of these diseases was attempted. In the first symptom group, >70% discrimination accuracy was obtained among symptomatic gallstones, pancreatitis, and cholecystitis, while for the second symptom group >85% classification accuracy was obtained for intestinal ischemia, strangulated obstruction, and mechanical obstruction. No single metabolite stands up as a possible biomarker for any of these diseases, while the contribution of the whole ¹H–NMR serum fingerprint seems to be a promising candidate, to be confirmed on larger cohorts, as a first-line discriminator for these diseases.

Creation and Characterization of a Genomically Hybrid Strain in the Nitrogen-Fixing Symbiotic Bacterium Sinorhizobium meliloti

Many bacteria, often associated with eukaryotic hosts and of relevance for biotechnological applications, harbor a multipartite genome composed of more than one replicon. Biotechnologically relevant phenotypes are often encoded by genes residing on the secondary replicons. A synthetic biology approach to developing enhanced strains for biotechnological purposes could therefore involve merging pieces or entire replicons from multiple strains into a single genome. Here we report the creation of a genomic hybrid strain in a model multipartite genome species, the plant-symbiotic bacterium Sinorhizobium meliloti. We term this strain as cis-hybrid, since it is produced by genomic material coming from the same species' pangenome. In particular, we moved the secondary replicon pSymA (accounting for nearly 20% of total genome content) from a donor S. meliloti strain to an acceptor strain. The cis-hybrid strain was screened for a panel of complex phenotypes (carbon/nitrogen utilization phenotypes, intra- and extracellular metabolomes, symbiosis, and various microbiological tests). Additionally, metabolic network reconstruction and constraint-based modeling were employed for in silico prediction of metabolic flux reorganization. Phenotypes of the cis-hybrid strain were in good agreement with those of both parental strains. Interestingly, the symbiotic phenotype showed a marked cultivar-specific improvement with the cis-hybrid strains compared to both parental strains. These results provide a proof-of-principle for the feasibility of genome-wide replicon-based remodelling of bacterial strains for improved biotechnological applications in precision agriculture.

Local and Global Dynamics in Intrinsically Disordered Synuclein

Intrinsically disordered proteins (IDPs) experience a diverse spectrum of motions that are difficult to characterize with a single experimental technique. Herein we combine high- and low-field nuclear spin relaxation, nanosecond fluorescence correlation spectroscopy (nsFCS), and long molecular dynamics simulations of alpha-synuclein, an IDP involved in Parkinson disease, to obtain a comprehensive picture of its conformational dynamics. The combined analysis shows that fast motions below 2 ns caused by local dihedral angle fluctuations and conformational sampling within and between Ramachandran substates decorrelate most of the backbone N-H orientational memory. However, slow motions with correlation times of up to ca. 13 ns from segmental dynamics are present throughout the alpha-synuclein chain, in particular in its C-terminal domain, and global chain reconfiguration occurs on a timescale of ca. 60 ns. Our study demonstrates a powerful strategy to determine residue-specific protein dynamics in IDPs at different time and length scales.

Dependence of apparent diffusion coefficient measurement on diffusion gradient direction and spatial position - A quality assurance intercomparison study of forty-four scanners for quantitative diffusion-weighted imaging

PURPOSE

To propose an MRI quality assurance procedure that can be used for routine controls and multi-centre comparison of different MR-scanners for quantitative diffusion-weighted imaging (DWI).

MATERIALS AND METHODS

44 MR-scanners with different field strengths (1 T, 1.5 T and 3 T) were included in the study. DWI acquisitions (b-value range 0-1000 s/mm²), with three different orthogonal diffusion gradient directions, were performed for each MR-scanner. All DWI acquisitions were performed by using a standard spherical plastic doped water phantom. Phantom solution ADC value and its dependence with temperature was measured using a DOSY sequence on a 600 MHz NMR spectrometer. Apparent diffusion coefficient (ADC) along each diffusion gradient direction and mean ADC were estimated, both at magnet isocentre and in six different position 50 mm away from isocentre, along positive and negative AP, RL and HF directions.

RESULTS

A good agreement was found between the nominal and measured mean ADC at isocentre: more than 90% of mean ADC measurements were within 5% from the nominal value, and the highest deviation was 11.3%. Away from isocentre, the effect of the diffusion gradient direction on ADC estimation was larger than 5% in 47% of included scanners and a spatial non uniformity larger than 5% was reported in 13% of centres.

CONCLUSION

ADC accuracy and spatial uniformity can vary appreciably depending on MR scanner model, sequence implementation (i.e. gradient diffusion direction) and hardware characteristics. The DWI quality assurance protocol proposed in this study can be employed in order to assess the accuracy and spatial uniformity of estimated ADC values, in single- as well as multi-centre studies.