US2018164290A1PendingUtilityA1

Nmr-based metabolite screening platform

Assignee: CHILDRENS MEDICAL CENTERPriority: Feb 10, 2012Filed: Mar 27, 2017Published: Jun 14, 2018
Est. expiryFeb 10, 2032(~5.5 yrs left)· nominal 20-yr term from priority
G01N 2458/15G01N 33/5038G01N 33/5005A61P 43/00G01N 24/08A61B 5/055G01R 33/465G01N 33/5011G01R 33/4633G01N 2570/00A61P 35/00G01N 2500/10
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Claims

Abstract

Methods that enable one to specifically measure the metabolic product of a particular molecule in relatively few cells, e.g. primary cells, are described. The methods involve optionally preloading cells with labeled substrate (e.g. labeled by 13 C, 15 N, or 31 P). The methods allow for easy identification of metabolites that are differentially generated in cells of different phenotypes. The new methods for unbiased multi-dimensional NMR screening and rapid and efficient analysis of the NMR screening identify differentially expressed metabolites in different cell or tissue types. Analysis of the differentially expressed metabolites can present unique druggable targets to which small molecule therapeutics can be designed.

Claims

exact text as granted — not AI-modified
What is claimed is: 
     
         1 . A method for monitoring metabolism of a substrate within a given type of cell in a sample, the method comprising:
 a. culturing a given type of cell of a first sample with a substrate for a sufficient period of time to allow metabolic breakdown of the substrate into substrate metabolites, wherein at least a portion of the substrate is optionally labeled with a nuclear magnetic resonance (NMR) stable isotope;   b. harvesting the substrate metabolites from the cells of step (a) to obtain a second sample of substrate metabolites; and   c. performing multi-dimensional NMR on the second sample of step (b) to determine a resonance spectrum of the metabolized substrate, wherein the resonance spectrum represents the metabolites of the substrate, and wherein the multi-dimensional NMR comprises any one of the following techniques: spectral width folding, random phase sampling, non-uniform sampling, and data extension for enhanced dynamic range data reconstruction.

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