36 research outputs found
The future of NMR-based metabolomics
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
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
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
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
Quantitative Lid Dynamics of MDM2 Reveals Differential Ligand Binding Modes of the p53-Binding Cleft
Modulation and Functional Role of the Orientations of the N- and P‑Domains of Cu<sup>+</sup>‑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<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
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
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