Real-time quantitative analysis of metabolic flux in live cells using a hyperpolarized micromagnetic resonance spectrometer. Academic Article uri icon

Overview

abstract

  • Metabolic reprogramming is widely considered a hallmark of cancer, and understanding metabolic dynamics described by the conversion rates or "fluxes" of metabolites can shed light onto biological processes of tumorigenesis and response to therapy. For real-time analysis of metabolic flux in intact cells or organisms, magnetic resonance (MR) spectroscopy and imaging methods have been developed in conjunction with hyperpolarization of nuclear spins. These approaches enable noninvasive monitoring of tumor progression and treatment efficacy and are being tested in multiple clinical trials. However, because of their limited sensitivity, these methods require a larger number of cells, on the order of 107, which is impractical for analyzing scant target cells or mass-limited samples. We present a new technology platform, a hyperpolarized micromagnetic resonance spectrometer (HMRS), that achieves real-time, 103-fold more sensitive metabolic analysis on live cells. This platform enables quantification of the metabolic flux in a wide range of cell types, including leukemia stem cells, without significant changes in viability, which allows downstream molecular analyses in tandem. It also enables rapid assessment of metabolic changes by a given drug, which may direct therapeutic choices in patients. We further advanced this platform for high-throughput analysis of hyperpolarized molecules by integrating a three-dimensionally printed microfluidic system. The HMRS platform holds promise as a sensitive method for studying metabolic dynamics in mass-limited samples, including primary cancer cells, providing novel therapeutic targets and an enhanced understanding of cellular metabolism.

publication date

  • June 16, 2017

Research

keywords

  • Energy Metabolism
  • Magnetic Resonance Spectroscopy

Identity

PubMed Central ID

  • PMC5473678

Scopus Document Identifier

  • 85041747594

Digital Object Identifier (DOI)

  • 10.1126/sciadv.1700341

PubMed ID

  • 28630930

Additional Document Info

volume

  • 3

issue

  • 6