36 research outputs found

    The future of NMR-based metabolomics

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    The two leading analytical approaches to metabolomics are mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. Although currently overshadowed by MS in terms of numbers of compounds resolved, NMR spectroscopy offers advantages both on its own and coupled with MS. NMR data are highly reproducible and quantitative over a wide dynamic range and are unmatched for determining structures of unknowns. NMR is adept at tracing metabolic pathways and fluxes using isotope labels. Moreover, NMR is non-destructive and can be utilized in vivo. NMR results have a proven track record of translating in vitro findings to in vivo clinical applications

    Order-Disorder Transitions Govern Kinetic Cooperativity and Allostery of Monomeric Human Glucokinase

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    Glucokinase (GCK) catalyzes the rate-limiting step of glucose catabolism in the pancreas, where it functions as the body's principal glucose sensor. GCK dysfunction leads to several potentially fatal diseases including maturity-onset diabetes of the young type II (MODY-II) and persistent hypoglycemic hyperinsulinemia of infancy (PHHI). GCK maintains glucose homeostasis by displaying a sigmoidal kinetic response to increasing blood glucose levels. This positive cooperativity is unique because the enzyme functions exclusively as a monomer and possesses only a single glucose binding site. Despite nearly a half century of research, the mechanistic basis for GCK's homotropic allostery remains unresolved. Here we explain GCK cooperativity in terms of large-scale, glucose-mediated disorder-order transitions using 17 isotopically labeled isoleucine methyl groups and three tryptophan side chains as sensitive nuclear magnetic resonance (NMR) probes. We find that the small domain of unliganded GCK is intrinsically disordered and samples a broad conformational ensemble. We also demonstrate that small-molecule diabetes therapeutic agents and hyperinsulinemia-associated GCK mutations share a strikingly similar activation mechanism, characterized by a population shift toward a more narrow, well-ordered ensemble resembling the glucose-bound conformation. Our results support a model in which GCK generates its cooperative kinetic response at low glucose concentrations by using a millisecond disorder-order cycle of the small domain as a "time-delay loop," which is bypassed at high glucose concentrations, providing a unique mechanism to allosterically regulate the activity of human GCK under physiological conditions.NIH [1R01DK081358]NIHNSF [MCB-0918362]NSFAmerican Heart AssociationAmerican Heart Associatio

    Nanoparticle-Assisted Metabolomics

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    Understanding and harnessing the interactions between nanoparticles and biological molecules is at the forefront of applications of nanotechnology to modern biology. Metabolomics has emerged as a prominent player in systems biology as a complement to genomics, transcriptomics and proteomics. Its focus is the systematic study of metabolite identities and concentration changes in living systems. Despite significant progress over the recent past, important challenges in metabolomics remain, such as the deconvolution of the spectra of complex mixtures with strong overlaps, the sensitive detection of metabolites at low abundance, unambiguous identification of known metabolites, structure determination of unknown metabolites and standardized sample preparation for quantitative comparisons. Recent research has demonstrated that some of these challenges can be substantially alleviated with the help of nanoscience. Nanoparticles in particular have found applications in various areas of bioanalytical chemistry and metabolomics. Their chemical surface properties and increased surface-to-volume ratio endows them with a broad range of binding affinities to biomacromolecules and metabolites. The specific interactions of nanoparticles with metabolites or biomacromolecules help, for example, simplify metabolomics spectra, improve the ionization efficiency for mass spectrometry or reveal relationships between spectral signals that belong to the same molecule. Lessons learned from nanoparticle-assisted metabolomics may also benefit other emerging areas, such as nanotoxicity and nanopharmaceutics

    Differential metabolism between biofilm and suspended Pseudomonas aeruginosa cultures in bovine synovial fluid by 2D NMR-based metabolomics

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    Total joint arthroplasty is a common surgical procedure resulting in improved quality of life; however, a leading cause of surgery failure is infection. Periprosthetic joint infections often involve biofilms, making treatment challenging. The metabolic state of pathogens in the joint space and mechanism of their tolerance to antibiotics and host defenses are not well understood. Thus, there is a critical need for increased understanding of the physiological state of pathogens in the joint space for development of improved treatment strategies toward better patient outcomes. Here, we present a quantitative, untargeted NMR-based metabolomics strategy for Pseudomonas aeruginosa suspended culture and biofilm phenotypes grown in bovine synovial fluid as a model system. Significant differences in metabolic pathways were found between the suspended culture and biofilm phenotypes including creatine, glutathione, alanine, and choline metabolism and the tricarboxylic acid cycle. We also identified 21 unique metabolites with the presence of P. aeruginosa in synovial fluid and one uniquely present with the biofilm phenotype in synovial fluid. If translatable in vivo, these unique metabolite and pathway differences have the potential for further to development to serve as targets for P. aeruginosa and biofilm control in synovial fluid

    Modulation and Functional Role of the Orientations of the N- and P‑Domains of Cu<sup>+</sup>‑Transporting ATPase along the Ion Transport Cycle

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    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<sup>+</sup>-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<sup>+</sup>-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

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

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    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

    Quantitative Analysis of Metabolic Mixtures by Two-Dimensional <sup>13</sup>C Constant-Time TOCSY NMR Spectroscopy

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    An increasing number of organisms can be fully <sup>13</sup>C-labeled, which has the advantage that their metabolomes can be studied by high-resolution two-dimensional (2D) NMR <sup>13</sup>C–<sup>13</sup>C constant-time (CT) total correlation spectroscopy (TOCSY) experiments. Individual metabolites can be identified via database searching or, in the case of novel compounds, through the reconstruction of their backbone-carbon topology. Determination of quantitative metabolite concentrations is another key task. Because strong peak overlaps in one-dimensional (1D) NMR spectra prevent straightforward quantification through 1D peak integrals, we demonstrate here the direct use of <sup>13</sup>C–<sup>13</sup>C CT-TOCSY spectra for metabolite quantification. This is accomplished through the quantum mechanical treatment of the TOCSY magnetization transfer at short and long-mixing times or by the use of analytical approximations, which are solely based on the knowledge of the carbon-backbone topologies. The methods are demonstrated for carbohydrate and amino acid mixtures
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