Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Parallel NMR Supersequences: Ten Spectra in a Single Measurement.

ABSTRACT: The principles employed in parallel NMR and MRI are applied to NMR supersequences yielding as many as ten 2D NMR spectra in one measurement. We present a number of examples where two NOAH (NMR by Ordered Acquisition using ¹H-detection) supersequences are recorded in parallel, thus dramatically increasing the information content obtained in a single NMR experiment. The two parallel supersequences entangled by time-sharing schemes (IPAP-seHSQC, HSQC-COSY, and HSQC-TOCSY) incorporate also modified (sequential and/or interleaved) conventional pulse schemes (modules), including HMBC, TOCSY, COSY, CLIP-COSY, NOESY, and ROESY. Such parallel supersequences can be tailored for specific applications, for instance, the analysis and characterization of molecular structure of complex organic molecules from a single measurement. In particular, the CASPER software was used to establish the structure of a tetrasaccharide, β-LNnTOMe, with a high degree of confidence from a single measurement involving a parallel NOAH-5 supersequence.

SUBMITTER: Kupce E

PROVIDER: S-EPMC8611666 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Parallel NMR Supersequences: Ten Spectra in a Single Measurement.

Kupče Ēriks Ē Yong Jonathan R J JRJ Widmalm Göran G Claridge Tim D W TDW

JACS Au 20211109 11

The principles employed in parallel NMR and MRI are applied to NMR supersequences yielding as many as ten 2D NMR spectra in one measurement. We present a number of examples where two NOAH (NMR by Ordered Acquisition using <sup>1</sup>H-detection) supersequences are recorded in parallel, thus dramatically increasing the information content obtained in a single NMR experiment. The two parallel supersequences entangled by time-sharing schemes (IPAP-seHSQC, HSQC-COSY, and HSQC-TOCSY) incorporate als ...[more]

PMID: 34841408

Similar Datasets

Rapid Measurement of Heteronuclear Coupling Constants in Complex NMR Spectra.

Project description:The NMR analysis of fluorine-containing molecules, increasingly widespread due to their importance in pharmaceuticals and biochemistry, poses significant challenges. Severe peak overlap in the proton spectrum often hinders the extraction of critical structural information in the form of heteronuclear scalar coupling constants, which are crucial for determining pharmaceutical properties and biological activity. Here, a new method, IPAP-FESTA, is reported that drastically simplifies measurements of the signs and magnitudes of proton-fluorine couplings. Its usefulness is demonstrated for the structural study of the steroidal drug fluticasone propionate extracted from a commercial formulation and for assessing solvent effects on the conformational equilibrium in a physically inseparable fluorohydrin mixture.

| S-EPMC10510310 | biostudies-literature

The NMR Spectral Measurement Database: A System for Organizing and Accessing NMR Spectra of Therapeutic Proteins.

Project description: Not available

| S-EPMC9683039 | biostudies-literature

Parallel measurement of dynamic changes in translation rates in single cells.

Project description:Protein concentrations are often regulated by dynamic changes in translation rates. Nevertheless, it has been challenging to directly monitor changes in translation in living cells. We have developed a reporter system to measure real-time changes of translation rates in human or mouse individual cells by conjugating translation regulatory motifs to sequences encoding a nuclear targeted fluorescent protein and a controllable destabilization domain. Application of the method showed that individual cells undergo marked fluctuations in the translation rate of mRNAs whose 5' terminal oligopyrimidine (5' TOP) motif regulates the synthesis of ribosomal proteins. Furthermore, we show that small reductions in amino acid levels signal through different mTOR-dependent pathways to control TOP mRNA translation, whereas larger reductions in amino acid levels control translation through eIF2A. Our study demonstrates that dynamic measurements of single-cell activities of translation regulatory motifs can be used to identify and investigate fundamental principles of translation.

| S-EPMC4039304 | biostudies-literature

NMR-TS: de novo molecule identification from NMR spectra.

Project description:Nuclear magnetic resonance (NMR) spectroscopy is an effective tool for identifying molecules in a sample. Although many previously observed NMR spectra are accumulated in public databases, they cover only a tiny fraction of the chemical space, and molecule identification is typically accomplished manually based on expert knowledge. Herein, we propose NMR-TS, a machine-learning-based python library, to automatically identify a molecule from its NMR spectrum. NMR-TS discovers candidate molecules whose NMR spectra match the target spectrum by using deep learning and density functional theory (DFT)-computed spectra. As a proof-of-concept, we identify prototypical metabolites from their computed spectra. After an average 5451 DFT runs for each spectrum, six of the nine molecules are identified correctly, and proximal molecules are obtained in the other cases. This encouraging result implies that de novo molecule generation can contribute to the fully automated identification of chemical structures. NMR-TS is available at https://github.com/tsudalab/NMR-TS.

| S-EPMC7476483 | biostudies-literature

Massively parallel single-molecule telomere length measurement with digital real-time PCR.

Project description:Telomere length is a promising biomarker for age-associated diseases and cancer, but there are still substantial challenges to routine telomere analysis in clinics because of the lack of a simple and rapid yet scalable method for measurement. We developed the single telomere absolute-length rapid (STAR) assay, a novel high-throughput digital real-time PCR approach for rapidly measuring the absolute lengths and quantities of individual telomere molecules. We show that this technique provides the accuracy and sensitivity to uncover associations between telomere length distribution and telomere maintenance mechanisms in cancer cell lines and primary tumors. The results indicate that the STAR assay is a powerful tool to enable the use of telomere length distribution as a biomarker in disease and population-wide studies.

| S-EPMC7442360 | biostudies-literature

Effect of Single-Walled Carbon Nanotube Association upon H NMR Spectra of Representative Organonitrogen Compounds.

Project description:This report is important to achieving SWCNT solvation, understanding adsorption of molecules on SWCNT surfaces, and SWCNT characterization by NMR. Complexation of 1-methyl-2-pyrrolidone (NMP) and other selected organonitrogens with single-walled carbon nanotubes (SWCNTs) was studied by proton nuclear magnetic resonance (NMR). The magnitude of (1)H NMR chemical shift change upon SWCNT:organonitrogen complex formation represents the strength of the association. Magnitudes of changes in NMR signals of different protons in the organonitrogen reveal which protons are in close proximity to SWCNTs. Results reveal that (1) in amides and aminoketones, SWCNT association with carbonyls is stronger than with nitrogen, (2) in aminoalcohols, SWCNT association with nitrogen is stronger than with oxygen, and (3) protons bonded to heteroatoms have greater changes in their chemical shifts than those bonded to carbons. Changes (broadening and downfield shifts) in (1)H NMR signals of the organonitrogen compounds, which accompany SWCNT:organonitrogen association, are dependent upon (1) type of proton within R (α, β, etc.), (2) proximity to the carbonyl (R-CO versus NR(2)), (3) steric effects of alkyls, (4) electronic effects of alkyls, and (5) effects of tethering two ends of a molecule.

| S-EPMC2894704 | biostudies-literature

Parallel measurement of transcriptomes and proteomes from same single cells using nanodroplet splitting.

Project description:Single-cell multiomics provides comprehensive insights into gene regulatory networks, cellular diversity, and temporal dynamics. Here, we introduce nanoSPLITS (nanodroplet SPlitting for Linked-multimodal Investigations of Trace Samples), an integrated platform that enables global profiling of the transcriptome and proteome from same single cells via RNA sequencing and mass spectrometry-based proteomics, respectively. Benchmarking of nanoSPLITS demonstrates high measurement precision with deep proteomic and transcriptomic profiling of single-cells. We apply nanoSPLITS to cyclin-dependent kinase 1 inhibited cells and found phospho-signaling events could be quantified alongside global protein and mRNA measurements, providing insights into cell cycle regulation. We extend nanoSPLITS to primary cells isolated from human pancreatic islets, introducing an efficient approach for facile identification of unknown cell types and their protein markers by mapping transcriptomic data to existing large-scale single-cell RNA sequencing reference databases. Accordingly, we establish nanoSPLITS as a multiomic technology incorporating global proteomics and anticipate the approach will be critical to furthering our understanding of biological systems.

| S-EPMC11621338 | biostudies-literature

The 100-protein NMR spectra dataset: A resource for biomolecular NMR data analysis.

Project description:Multidimensional NMR spectra are the basis for studying proteins by NMR spectroscopy and crucial for the development and evaluation of methods for biomolecular NMR data analysis. Nevertheless, in contrast to derived data such as chemical shift assignments in the BMRB and protein structures in the PDB databases, this primary data is in general not publicly archived. To change this unsatisfactory situation, we present a standardized set of solution NMR data comprising 1329 2-4-dimensional NMR spectra and associated reference (chemical shift assignments, structures) and derived (peak lists, restraints for structure calculation, etc.) annotations. With the 100-protein NMR spectra dataset that was originally compiled for the development of the ARTINA deep learning-based spectra analysis method, 100 protein structures can be reproduced from their original experimental data. The 100-protein NMR spectra dataset is expected to help the development of computational methods for NMR spectroscopy, in particular machine learning approaches, and enable consistent and objective comparisons of these methods.

| S-EPMC10767026 | biostudies-literature

SC3-seq: a method for highly parallel and quantitative measurement of single-cell gene expression.

Project description:Single-cell mRNA sequencing (RNA-seq) methods have undergone rapid development in recent years, and transcriptome analysis of relevant cell populations at single-cell resolution has become a key research area of biomedical sciences. We here present single-cell mRNA 3-prime end sequencing (SC3-seq), a practical methodology based on PCR amplification followed by 3-prime-end enrichment for highly quantitative, parallel and cost-effective measurement of gene expression in single cells. The SC3-seq allows excellent quantitative measurement of mRNAs ranging from the 10,000-cell to 1-cell level, and accordingly, allows an accurate estimate of the transcript levels by a regression of the read counts of spike-in RNAs with defined copy numbers. The SC3-seq has clear advantages over other typical single-cell RNA-seq methodologies for the quantitative measurement of transcript levels and at a sequence depth required for the saturation of transcript detection. The SC3-seq distinguishes four distinct cell types in the peri-implantation mouse blastocysts. Furthermore, the SC3-seq reveals the heterogeneity in human-induced pluripotent stem cells (hiPSCs) cultured under on-feeder as well as feeder-free conditions, demonstrating a more homogeneous property of the feeder-free hiPSCs. We propose that SC3-seq might be used as a powerful strategy for single-cell transcriptome analysis in a broad range of investigations in biomedical sciences.

| S-EPMC4482058 | biostudies-literature