Imbalance in Glucose Metabolism Regulates the Transition of Microglia from Homeostasis to Disease-Associated Microglia Stage 1.

Microglia undergo two-stage activation in neurodegenerative diseases, known as disease-associated microglia (DAM). TREM2 mediates the DAM2 stage transition, but what regulates the first DAM1 stage transition is unknown. We report that glucose dyshomeostasis inhibits DAM1 activation and PKM2 plays a role. As in tumors, PKM2 was aberrantly elevated in both male and female human AD brains, but unlike in tumors, it is expressed as active tetramers, as well as among TREM2+ microglia surrounding plaques in 5XFAD male and female mice. snRNAseq analyses of microglia without Pkm2 in 5XFAD mice revealed significant increases in DAM1 markers in a distinct metabolic cluster, which is enriched in genes for glucose metabolism, DAM1, and AD risk. 5XFAD mice incidentally exhibited a significant reduction in amyloid pathology without microglial Pkm2 Surprisingly, microglia in 5XFAD without Pkm2 exhibited increases in glycolysis and spare respiratory capacity, which correlated with restoration of mitochondrial cristae alterations. In addition, in situ spatial metabolomics of plaque-bearing microglia revealed an increase in respiratory activity. These results together suggest that it is not only glycolytic but also respiratory inputs that are critical to the development of DAM signatures in 5XFAD mice.

Fundamental and practical aspects of machine learning for the peak picking of biomolecular NMR spectra.

Rapid progress in machine learning offers new opportunities for the automated analysis of multidimensional NMR spectra ranging from protein NMR to metabolomics applications. Most recently, it has been demonstrated how deep neural networks (DNN) designed for spectral peak picking are capable of deconvoluting highly crowded NMR spectra rivaling the facilities of human experts. Superior DNN-based peak picking is one of a series of critical steps during NMR spectral processing, analysis, and interpretation where machine learning is expected to have a major impact. In this perspective, we lay out some of the unique strengths as well as challenges of machine learning approaches in this new era of automated NMR spectral analysis. Such a discussion seems timely and should help define common goals for the NMR community, the sharing of software tools, standardization of protocols, and calibrate expectations. It will also help prepare for an NMR future where machine learning and artificial intelligence tools will be common place.

COLMARq: A Web Server for 2D NMR Peak Picking and Quantitative Comparative Analysis of Cohorts of Metabolomics Samples.

Highly quantitative metabolomics studies of complex biological mixtures are facilitated by the resolution enhancement afforded by 2D NMR spectra such as 2D 13C-1H HSQC spectra. Here, we describe a new public web server, COLMARq, for the semi-automated analysis of sets of 2D HSQC spectra of cohorts of samples. The workflow of COLMARq includes automated peak picking using the deep neural network DEEP Picker, quantitative cross-peak volume extraction by numerical fitting using Voigt Fitter, the matching of corresponding cross-peaks across cohorts of spectra, peak volume normalization between different spectra, database query for metabolite identification, and basic univariate and multivariate statistical analyses of the results. COLMARq allows the analysis of cross-peaks that belong to both known and unknown metabolites. After a user has uploaded cohorts of 2D 13C-1H HSQC and optionally 2D 1H-1H TOCSY spectra in their preferred format, all subsequent steps on the web server can be performed fully automatically, allowing manual editing if needed and the sessions can be saved for later use. The accuracy, versatility, and interactive nature of COLMARq enables quantitative metabolomics analysis, including biomarker identification, of a broad range of complex biological mixtures as is illustrated for cohorts of samples from bacterial cultures of Pseudomonas aeruginosa in both its biofilm and planktonic states.

Observation of Sub-Microsecond Protein Methyl-Side Chain Dynamics by Nanoparticle-Assisted NMR Spin Relaxation.

Amino-acid side-chain properties in proteins are key determinants of protein function. NMR spin relaxation of side chains is an important source of information about local protein dynamics and flexibility. However, traditional solution NMR relaxation methods are most sensitive to sub-nanosecond dynamics lacking information on slower ns-µs time-scale motions. Nanoparticle-assisted NMR spin relaxation (NASR) of methyl-side chains is introduced here as a window into these ns-µs dynamics. NASR utilizes the transient and nonspecific interactions between folded proteins and slowly tumbling spherical nanoparticles (NPs), whereby the increase of the relaxation rates reflects motions on time scales from ps all the way to the overall tumbling correlation time of the NPs ranging from hundreds of ns to µs. The observed motional amplitude of each methyl group can then be expressed by a model-free NASR S2 order parameter. The method is demonstrated for 2H-relaxation of CH2D methyl moieties and cross-correlated relaxation of CH3 groups for proteins Im7 and ubiquitin in the presence of anionic silica-nanoparticles. Both types of relaxation experiments, dominated by either quadrupolar or dipolar interactions, yield highly consistent results. Im7 shows additional dynamics on the intermediate time scales taking place in a functionally important loop, whereas ubiquitin visits the majority of its conformational substates on the sub-ns time scale. These experimental observations are in good agreement with 4-10 µs all-atom molecular dynamics trajectories. NASR probes side-chain dynamics on a much wider range of motional time scales than previously possible, thereby providing new insights into the interplay between protein structure, dynamics, and molecular interactions that govern protein function.

2D NMR-Based Metabolomics with HSQC/TOCSY NOAH Supersequences.

Sensitivity-improved versions of two-dimensional (2D) 13C-1H HSQC (heteronuclear single quantum coherence) and HSQC-TOCSY (HSQC-total correlation spectroscopy) NMR experiments optimized for small biological molecules and their complex mixtures encountered in metabolomics are presented that preserve the magnetization of 1H spins not directly attached to 13C spins. This allows (i) the application of rapid acquisition techniques to substantially shorten measurement time and (ii) their incorporation into supersequences (NOAH-NMR by ordered acquisition using 1H detection) for the compact acquisition of multiple 2D NMR data sets with significant gains in sensitivity, resolution, and/or time. The new pulse sequences, which are demonstrated for both metabolite model mixtures and mouse urine, offer an attractive approach for the efficient measurement of multiple 2D NMR spectra (HSQCsi and/or HSQCsi-TOCSY and TOCSY) of metabolomics samples in a single experiment for the accurate and comprehensive identification and quantitation of metabolites. These new methods bring to bear the advantages of 2D NMR to metabolomics studies with larger cohorts of samples.

Broadband Dynamics of Ubiquitin by Anionic and Cationic Nanoparticle Assisted NMR Spin Relaxation.

The quantitative and comprehensive description of the internal dynamics of proteins is critical for understanding their function. Nanoparticle-assisted 15 N NMR spin relaxation spectroscopy is a new method for the observation of picosecond to microsecond dynamics of proteins when transiently interacting with the surface of the nanoparticles (NPs). The method is applied here to the protein ubiquitin in the presence of anionic and cationic silica NPs (SNPs) of different sizes. The backbone dynamics profiles are reproducible and strikingly similar to each other, indicating that specific protein-SNP interactions are unimportant. The dynamics profiles closely match the sub-nanosecond dynamics S2 values observed by model-free analysis of standard 15 N relaxation of ubiquitin in free solution, indicating that the bulk of the ubiquitin backbone dynamics in solution is confined to sub-nanosecond timescales and, hence, it is dynamically more restrained than previous NMR studies have suggested.

COLMAR Lipids Web Server and Ultrahigh-Resolution Methods for Two-Dimensional Nuclear Magnetic Resonance- and Mass Spectrometry-Based Lipidomics.

Accurate identification of lipids in biological samples is a key step in lipidomics studies. Multidimensional nuclear magnetic resonance (NMR) spectroscopy is a powerful analytical tool for this purpose as it provides comprehensive structural information on lipid composition at atomic resolution. However, the interpretation of NMR spectra of complex lipid mixtures is currently hampered by limited spectral resolution and the absence of a customized lipid NMR database along with user-friendly spectral analysis tools. We introduce a new two-dimensional (2D) NMR metabolite database "COLMAR Lipids" that was specifically curated for hydrophobic metabolites presently containing 501 compounds with accurate experimental 2D 13C-1H heteronuclear single quantum coherence (HSQC) chemical shift data measured in CDCl3. A new module in the public COLMAR suite of NMR web servers was developed for the (semi)automated analysis of complex lipidomics mixtures (http://spin.ccic.osu.edu/index.php/colmarm/index2). To obtain 2D HSQC spectra with the necessary high spectral resolution along both 13C and 1H dimensions, nonuniform sampling in combination with pure shift spectroscopy was applied allowing the extraction of an abundance of unique cross-peaks belonging to hydrophobic compounds in complex lipidomics mixtures. As shown here, this information is critical for the unambiguous identification of underlying lipid molecules by means of the new COLMAR Lipids web server, also in combination with mass spectrometry, as is demonstrated for Caco-2 cell and lung tissue cell extracts.

Extreme Nonuniform Sampling for Protein NMR Dynamics Studies in Minimal Time.

NMR spectroscopy is an extraordinarily rich source of quantitative dynamics of proteins in solution using spin relaxation or chemical exchange saturation transfer (CEST) experiments. However, 15N-CEST measurements require prolonged multidimensional, so-called pseudo-3D HSQC experiments where the pseudo dimension is a radio frequency offset Δω of a weak 15N saturation field. Nonuniform sampling (NUS) approaches have the potential to significantly speed up these measurements, but they also carry the risk of introducing serious artifacts and the systematic optimization of nonuniform sampling schedules has remained elusive. It is demonstrated here how this challenge can be addressed by using fitted cross-peaks of a reference 2D HSQC experiment as footprints, which are subsequently used to reconstruct cross-peak amplitudes of a pseudo-3D data set as a function of Δω by a linear least-squares fit. It is shown for protein Im7 how the approach can yield highly accurate CEST profiles based on an absolutely minimally sampled (AMS) data set allowing a speed-up of a factor 20-30. Spectrum-specific optimized nonuniform sampling (SONUS) schemes based on the Cramer-Rao lower bound metric were critical to achieve such a performance, revealing also more general properties of optimal sampling schedules. This is the first systematic exploration and optimization of NUS schedules for the dramatic speed-up of quantitative multidimensional NMR measurements that minimize unwanted errors.

Real-Time Pure Shift HSQC NMR for Untargeted Metabolomics.

Sensitivity and resolution are key considerations for NMR applications in general and for metabolomics in particular, where complex mixtures containing hundreds of metabolites over a large range of concentrations are commonly encountered. There is a strong demand for advanced methods that can provide maximal information in the shortest possible time frame. Here, we present the optimization and application of the recently introduced 2D real-time BIRD 1H-13C HSQC experiment for NMR-based metabolomics of aqueous samples at 13C natural abundance. For mouse urine samples, it is demonstrated how this real-time pure shift sensitivity-improved heteronuclear single quantum correlation method provides broadband homonuclear decoupling along the proton detection dimension and thereby significantly improves spectral resolution in regions that are affected by spectral overlap. Moreover, the collapse of the scalar multiplet structure of cross-peaks leads to a sensitivity gain of about 40-50% over a traditional 2D HSQC-SI experiment. The experiment works well over a range of magnetic field strengths and is particularly useful when resonance overlap in crowded regions of the HSQC spectra hampers accurate metabolite identification and quantitation.

Accurate and Efficient Determination of Unknown Metabolites in Metabolomics by NMR-Based Molecular Motif Identification.

Knowledge of the chemical identity of metabolite molecules is critical for the understanding of the complex biological systems to which they belong. Since metabolite identities and their concentrations are often directly linked to the phenotype, such information can be used to map biochemical pathways and understand their role in health and disease. A very large number of metabolites however are still unknown; i.e., their spectroscopic signatures do not match those in existing databases, suggesting unknown molecule identification is both imperative and challenging. Although metabolites are structurally highly diverse, the majority shares a rather limited number of structural motifs, which are defined by sets of 1H and 13C chemical shifts of the same spin system. This allows one to characterize unknown metabolites by a divide-and-conquer strategy that identifies their structural motifs first. Here, we present the structural motif-based approach "SUMMIT Motif" for the de novo identification of unknown molecular structures in complex mixtures, without the need for extensive purification, using NMR in tandem with two newly curated NMR molecular structural motif metabolomics databases (MSMMDBs). For the identification of structural motif(s), first, the 1H and 13C chemical shifts of all the individual spin systems are extracted from 2D and 3D NMR spectra of the complex mixture. Next, the molecular structural motifs are identified by querying these chemical shifts against the new MSMMDBs. One database, COLMAR MSMMDB, was derived from experimental NMR chemical shifts of known metabolites taken from the COLMAR metabolomics database, while the other MSMMDB, pNMR MSMMDB, is based on predicted chemical shifts of metabolites of several existing large metabolomics databases. For molecules consisting of multiple spin systems, spin systems are connected via long-range scalar J-couplings. When this motif-based identification method was applied to the hydrophilic extract of mouse bile fluid, two unknown metabolites could be successfully identified. This approach is both accurate and efficient for the identification of unknown metabolites and hence enables the discovery of new biochemical processes and potential biomarkers.

The Intracellular Loop of the Na+/Ca2+ Exchanger Contains an "Awareness Ribbon"-Shaped Two-Helix Bundle Domain.

The Na+/Ca2+ exchanger (NCX) is a ubiquitous single-chain membrane protein that plays a major role in regulating the intracellular Ca2+ homeostasis by the counter transport of Na+ and Ca2+ across the cell membrane. Other than its prokaryotic counterpart, which contains only the transmembrane domain and is self-sufficient as an active ion transporter, the eukaryotic NCX protein possesses in addition a large intracellular loop that senses intracellular calcium signals and controls the activation of ion transport across the membrane. This provides a necessary layer of regulation for the more complex function of eukaryotic cells. The Ca2+ sensor in the intracellular loop is known as the Ca2+-binding domain (CBD12). However, how the signaling of the allosteric intracellular Ca2+ binding propagates and results in transmembrane ion transportation still lacks a detailed explanation. Further structural and dynamics characterization of the intracellular loop flanking both sides of CBD12 is therefore imperative. Here, we report the identification and characterization of another structured domain that is N-terminal to CBD12 in the intracellular loop using solution nuclear magnetic resonance (NMR) spectroscopy. The atomistic structure of this domain reveals that two tandem long α-helices, connected by a short linker, form a stable crossover two-helix bundle (THB), resembling an "awareness ribbon". Considering the highly conserved amino acid sequence of the THB domain, the detailed structural and dynamics properties of the THB domain will be common among NCXs from different species and will contribute toward the understanding of the regulatory mechanism of eukaryotic Na+/Ca2+ exchangers.

Time-Resolved Protein Side-Chain Motions Unraveled by High-Resolution Relaxometry and Molecular Dynamics Simulations.

Motions of proteins are essential for the performance of their functions. Aliphatic protein side chains and their motions play critical roles in protein interactions: for recognition and binding of partner molecules at the surface or serving as an entropy reservoir within the hydrophobic core. Here, we present a new NMR method based on high-resolution relaxometry and high-field relaxation to determine quantitatively both motional amplitudes and time scales of methyl-bearing side chains in the picosecond-to-nanosecond range. We detect a wide variety of motions in isoleucine side chains in the protein ubiquitin. We unambiguously identify slow motions in the low nanosecond range, which, in conjunction with molecular dynamics computer simulations, could be assigned to transitions between rotamers. Our approach provides unmatched detailed insight into the motions of aliphatic side chains in proteins and provides a better understanding of the nature and functional role of protein side-chain motions.

miRNA-122 Protects Mice and Human Hepatocytes from Acetaminophen Toxicity by Regulating Cytochrome P450 Family 1 Subfamily A Member 2 and Family 2 Subfamily E Member 1 Expression.

Acetaminophen toxicity is a leading cause of acute liver failure (ALF). We found that miRNA-122 (miR-122) is down-regulated in liver biopsy specimens of patients with ALF and in acetaminophen-treated mice. A marked decrease in the primary miR-122 expression occurs in mice on acetaminophen overdose because of suppression of its key transactivators, hepatocyte nuclear factor (HNF)-4α and HNF6. More importantly, the mortality rates of male and female liver-specific miR-122 knockout (LKO) mice were significantly higher than control mice when injected i.p. with an acetaminophen dose not lethal to the control. LKO livers exhibited higher basal expression of cytochrome P450 family 2 subfamily E member 1 (CYP2E1) and cytochrome P450 family 1 subfamily A member 2 (CYP1A2) that convert acetaminophen to highly reactive N-acetyl-p-benzoquinone imine. Upregulation of Cyp1a2 primary transcript and mRNA in LKO mice correlated with the elevation of aryl hydrocarbon receptor (AHR) and mediator 1 (MED1), two transactivators of Cyp1a2. Analysis of ChIP-seq data in the ENCODE (Encyclopedia of DNA Element) database identified association of CCCTC-binding factor (CTCF) with Ahr promoter in mouse livers. Both MED1 and CTCF are validated conserved miR-122 targets. Furthermore, depletion of Ahr, Med1, or Ctcf in Mir122-/- hepatocytes reduced Cyp1a2 expression. Pulse-chase studies found that CYP2E1 protein level is upregulated in LKO hepatocytes. Notably, miR-122 depletion sensitized differentiated human HepaRG cells to acetaminophen toxicity that correlated with upregulation of AHR, MED1, and CYP1A2 expression. Collectively, these results reveal a critical role of miR-122 in acetaminophen detoxification and implicate its therapeutic potential in patients with ALF.

Non-Uniform and Absolute Minimal Sampling for High-Throughput Multidimensional NMR Applications.

Many biomolecular NMR applications can benefit from the faster acquisition of multidimensional NMR data with high resolution and their automated analysis and interpretation. In recent years, a number of non-uniform sampling (NUS) approaches have been introduced for the reconstruction of multidimensional NMR spectra, such as compressed sensing, thereby bypassing traditional Fourier-transform processing. Such approaches are applicable to both biomacromolecules and small molecules and their complex mixtures and can be combined with homonuclear decoupling (pure shift) and covariance processing. For homonuclear 2D TOCSY experiments, absolute minimal sampling (AMS) permits the drastic shortening of measurement times necessary for high-throughput applications for identification and quantification of components in complex biological mixtures in the field of metabolomics. Such TOCSY spectra can be comprehensively represented by graphic theoretical maximal cliques for the identification of entire spin systems and their subsequent query against NMR databases. Integration of these methods in webservers permits the rapid and reliable identification of mixture components. Recent progress is reviewed in this Minireview.

Accurate Identification of Unknown and Known Metabolic Mixture Components by Combining 3D NMR with Fourier Transform Ion Cyclotron Resonance Tandem Mass Spectrometry.

Metabolite identification in metabolomics samples is a key step that critically impacts downstream analysis. We recently introduced the SUMMIT NMR/mass spectrometry (MS) hybrid approach for the identification of the molecular structure of unknown metabolites based on the combination of NMR, MS, and combinatorial cheminformatics. Here, we demonstrate the feasibility of the approach for an untargeted analysis of both a model mixture and E. coli cell lysate based on 2D/3D NMR experiments in combination with Fourier transform ion cyclotron resonance MS and MS/MS data. For 19 of the 25 model metabolites, SUMMIT yielded complete structures that matched those in the mixture independent of database information. Of those, seven top-ranked structures matched those in the mixture, and four of those were further validated by positive ion MS/MS. For five metabolites, not part of the 19 metabolites, correct molecular structural motifs could be identified. For E. coli, SUMMIT MS/NMR identified 20 previously known metabolites with three or more 1H spins independent of database information. Moreover, for 15 unknown metabolites, molecular structural fragments were determined consistent with their spin systems and chemical shifts. By providing structural information for entire metabolites or molecular fragments, SUMMIT MS/NMR greatly assists the targeted or untargeted analysis of complex mixtures of unknown compounds.

The Michaelis Complex of Arginine Kinase Samples the Transition State at a Frequency That Matches the Catalytic Rate.

Arginine kinase (AK), which is a member of the phosphagen kinase family, serves as a model system for studying the structural and dynamic determinants of biomolecular enzyme catalysis of all major states involved of the enzymatic cycle. These states are the apo state (substrate free), the Michaelis complex analogue AK:Arg:Mg·AMPPNP (MCA), a product complex analogue AK:pAIE:Mg·ADP (PCA), and the transition state analogue AK:Arg:Mg·ADP:NO3- (TSA). The conformational dynamics of these states have been studied by NMR relaxation dispersion measurements of the methyl groups of the Ile, Leu, and Val residues at two static magnetic fields. Although all states undergo significant amounts of µs-ms time scale dynamics, only the MCA samples a dominant excited state that resembles the TSA, as evidenced by the strong correlation between the relaxation dispersion derived chemical shift differences Δω and the equilibrium chemical shift differences Δδ of these states. The average lifetime of the MCA is 36 ms and the free energy difference to the TSA-like form is 8.5 kJ/mol. It is shown that the conformational energy landscape of the Michaelis complex analogue is shaped in a way that at room temperature it channels passage to the transition state, thereby determining the rate-limiting step of the phosphorylation reaction of arginine. Conversely, relaxation dispersion experiments of the TSA reveal that it samples the structures of the Michaelis complex analogue or the apo state as its dominant excited state. This reciprocal behavior shows that the free energy of the TSA, with all ligands bound, is lower by only about 8.9 kJ/mol than that of the Michaelis or apo complex conformations with the TSA ligands present.

Model for the allosteric regulation of the Na+/Ca2+ exchanger NCX.

The Na(+) /Ca(2+) exchanger provides a major Ca(2+) extrusion pathway in excitable cells and plays a key role in the control of intracellular Ca(2+) concentrations. In Canis familiaris, Na(+) /Ca(2+) exchanger (NCX) activity is regulated by the binding of Ca(2+) to two cytosolic Ca(2+) -binding domains, CBD1 and CBD2, such that Ca(2+) -binding activates the exchanger. Despite its physiological importance, little is known about the exchanger's global structure, and the mechanism of allosteric Ca(2+) -regulation remains unclear. It was found previously that for NCX in the absence of Ca(2+) the two domains CBD1 and CBD2 of the cytosolic loop are flexibly linked, while after Ca(2+) -binding they adopt a rigid arrangement that is slightly tilted. A realistic model for the mechanism of the exchanger's allosteric regulation should not only address this property, but also it should explain the distinctive behavior of Drosophila melanogaster's sodium/calcium exchanger, CALX, for which Ca(2+) -binding to CBD1 inhibits Ca(2+) exchange. Here, NMR spin relaxation and residual dipolar couplings were used to show that Ca(2+) modulates CBD1 and CBD2 interdomain flexibility of CALX in an analogous way as for NCX. A mechanistic model for the allosteric Ca(2+) regulation of the Na(+) /Ca(2+) exchanger is proposed. In this model, the intracellular loop acts as an entropic spring whose strength is modulated by Ca(2+) -binding to CBD1 controlling ion transport across the plasma membrane.

Nanoparticle-Assisted Removal of Protein in Human Serum for Metabolomics Studies.

Among human body fluids, serum plays a key role for diagnostic tests and, increasingly, for metabolomics analysis. However, the high protein content of serum poses significant challenges for nuclear magnetic resonance (NMR)-based metabolomics studies because it can strongly interfere with metabolite signal detection and quantitation. Although several methods for protein removal have been proposed, including ultrafiltration and organic-solvent-induced protein precipitation, there is currently no standard operating procedure for the elimination of protein from human serum samples. Here, we introduce novel procedures for the removal of protein from serum by the addition of nanoparticles. It is demonstrated how serum protein can be efficiently, cost-effectively, and environmentally friendly removed at physiological pH (pH 7.4) through attractive interactions with silica nanoparticles. It is further shown how serum can be processed with nanoparticles prior to ultrafiltration or organic-solvent-induced protein precipitation for optimal protein removal. After examination of all of the procedures, the combination of nanoparticle treatment and ultrafiltration is found to have a minimal effect on the metabolite content, leading to remarkably clean homo- and heteronuclear NMR spectra of the serum metabolome that compare favorably to other methods for protein removal.

Modulation and Functional Role of the Orientations of the N- and P-Domains of Cu+ -Transporting ATPase along the Ion Transport Cycle.

Ion transport of different P-type ATPases is regulated similarly through the interplay of multiple protein domains. In the presence of ATP, binding of a cation to the ion binding site in the transmembrane helices leads to the phosphorylation of the P-domain, allowing ion transfer across the membrane. The details of the mechanism, however, are not clear. Here, we report the modulation of the orientation between the N- and P-domains of Cu(+)-transporting ATPase along the ion transport cycle using high-resolution nuclear magnetic resonance spectroscopy in solution. On the basis of residual dipolar coupling measurements, it is found that the interdomain orientation (relative openness) of the N- and P-domains is distinctly modulated depending on the specific state of the N- and P-domains along the ion translocation cycle. The two domains' relative position in the apo state is semiopen, whereas it becomes closed upon binding of ATP to the N-domain. After phosphorylation of the P-domain and the release of ADP, the opening, however, becomes the widest among all the states. We reason such wide opening resulting from the departure of ADP prepares the N- and P-domains to accommodate the A-domain for interaction and, hence, promote ion transport and allow dephosphorylation of the P-domain. Such wide interdomain opening is abolished when an Asn to Asp mutation is introduced into the conserved DXXK motif located in the hinge region of the N- and P-domains of Cu(+)-ATPase, suggesting the indispensible role of the N- and P-interdomain orientation during ion transportation. Our results shed new light on the structural and mechanistic details of P-type ATPase function at large.

Metabolomics beyond spectroscopic databases: a combined MS/NMR strategy for the rapid identification of new metabolites in complex mixtures.

A novel strategy is introduced that combines high-resolution mass spectrometry (MS) with NMR for the identification of unknown components in complex metabolite mixtures encountered in metabolomics. The approach first identifies the chemical formulas of the mixture components from accurate masses by MS and then generates all feasible structures (structural manifold) that are consistent with these chemical formulas. Next, NMR spectra of each member of the structural manifold are predicted and compared with the experimental NMR spectra in order to identify the molecular structures that match the information obtained from both the MS and NMR techniques. This combined MS/NMR approach was applied to Escherichia coli extract, where the approach correctly identified a wide range of different types of metabolites, including amino acids, nucleic acids, polyamines, nucleosides, and carbohydrate conjugates. This makes this approach, which is termed SUMMIT MS/NMR, well suited for high-throughput applications for the discovery of new metabolites in biological and biomedical mixtures, overcoming the need of experimental MS and NMR metabolite databases.