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Fast exchange fluxes around the pyruvate node: a leaky cell model to explain the gain and loss of unlabelled and labelled metabolites in a tracer experiment

Overview of attention for article published in Cancer & Metabolism, July 2016
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Title
Fast exchange fluxes around the pyruvate node: a leaky cell model to explain the gain and loss of unlabelled and labelled metabolites in a tracer experiment
Published in
Cancer & Metabolism, July 2016
DOI 10.1186/s40170-016-0153-9
Pubmed ID
Authors

Lake-Ee Quek, Menghan Liu, Sanket Joshi, Nigel Turner

Abstract

Glucose and glutamine are the two dominant metabolic substrates in cancer cells. In (13)C tracer experiments, however, it is necessary to account for all significant input substrates, as some natural (unlabelled) substrate in the medium, often derived from serum, can be metabolised by cells despite not showing signs of net consumption. Using [U-(13)C6]-glucose tracers and measuring extracellular metabolite enrichments by GC-MS, we found that pancreatic cells HPDE and PANC-1 secrete lactate, pyruvate, TCA cycle metabolites and non-essential amino acids synthesised from glucose. Focusing our investigations on pyruvate exchange in HEK293 cells, we observed that the four metabolites pools, intracellular and extracellular lactate and pyruvate, had similar (13)C enrichment trajectories. This indicated that these metabolites can mix rapidly. Using a hybrid (13)C-MFA, we followed to show that the lactate exchange flux had increased when extracellular lactate concentration was increased by 10-fold. By allowing rapid exchange fluxes around the pyruvate node, (13)C-MFA revealed that PANC-1 cells cultured in [U-(13)C6]-glucose doubled the conversion of unlabelled substrates to pyruvate when treated with TNF-α. The current work established the possibility that a cell's range of significant input substrates may be broader than anticipated. Metabolite exchange can affect intracellular enrichments. In particular, we showed that pyruvate was more strongly connected to lactate than to upstream glycolytic intermediates and that a fast lactate exchange may alter the outcome of flux analyses. Nevertheless, the leaky cell model may be an opportunity in disguise-the ability to continuously monitor metabolism using only the enrichments of extracellular metabolites.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 38%
Student > Bachelor 3 13%
Researcher 3 13%
Student > Postgraduate 2 8%
Student > Master 1 4%
Other 3 13%
Unknown 3 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 29%
Medicine and Dentistry 2 8%
Computer Science 2 8%
Agricultural and Biological Sciences 1 4%
Unspecified 1 4%
Other 5 21%
Unknown 6 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 July 2016.
All research outputs
#20,335,423
of 22,880,230 outputs
Outputs from Cancer & Metabolism
#183
of 204 outputs
Outputs of similar age
#307,430
of 354,139 outputs
Outputs of similar age from Cancer & Metabolism
#6
of 6 outputs
Altmetric has tracked 22,880,230 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 204 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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