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Metabolomic changes during cellular transformation monitored by metabolite–metabolite correlation analysis and correlated with gene expression
To investigate metabolic changes during cellular transformation, we used a (1)H NMR based metabolite–metabolite correlation analysis (MMCA) method, which permits analysis of homeostatic mechanisms in cells at the steady state, in an inducible cell transformation model. Transcriptomic data were used...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4605990/ https://www.ncbi.nlm.nih.gov/pubmed/26491426 http://dx.doi.org/10.1007/s11306-015-0838-z |
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author | Madhu, Basetti Narita, Masako Jauhiainen, Alexandra Menon, Suraj Stubbs, Marion Tavaré, Simon Narita, Masashi Griffiths, John R. |
author_facet | Madhu, Basetti Narita, Masako Jauhiainen, Alexandra Menon, Suraj Stubbs, Marion Tavaré, Simon Narita, Masashi Griffiths, John R. |
author_sort | Madhu, Basetti |
collection | PubMed |
description | To investigate metabolic changes during cellular transformation, we used a (1)H NMR based metabolite–metabolite correlation analysis (MMCA) method, which permits analysis of homeostatic mechanisms in cells at the steady state, in an inducible cell transformation model. Transcriptomic data were used to further explain the results. Transformed cells showed many more metabolite–metabolite correlations than control cells. Some had intuitively plausible explanations: a shift from glycolysis to amino acid oxidation after transformation was accompanied by a strongly positive correlation between glucose and glutamine and a strongly negative one between lactate and glutamate; there were also many correlations between the branched chain amino acids and the aromatic amino acids. Others remain puzzling: after transformation strong positive correlations developed between choline and a group of five amino acids, whereas the same amino acids showed negative correlations with phosphocholine, a membrane phospholipid precursor. MMCA in conjunction with transcriptome analysis has opened a new window into the metabolome. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-015-0838-z) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4605990 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-46059902015-10-19 Metabolomic changes during cellular transformation monitored by metabolite–metabolite correlation analysis and correlated with gene expression Madhu, Basetti Narita, Masako Jauhiainen, Alexandra Menon, Suraj Stubbs, Marion Tavaré, Simon Narita, Masashi Griffiths, John R. Metabolomics Original Article To investigate metabolic changes during cellular transformation, we used a (1)H NMR based metabolite–metabolite correlation analysis (MMCA) method, which permits analysis of homeostatic mechanisms in cells at the steady state, in an inducible cell transformation model. Transcriptomic data were used to further explain the results. Transformed cells showed many more metabolite–metabolite correlations than control cells. Some had intuitively plausible explanations: a shift from glycolysis to amino acid oxidation after transformation was accompanied by a strongly positive correlation between glucose and glutamine and a strongly negative one between lactate and glutamate; there were also many correlations between the branched chain amino acids and the aromatic amino acids. Others remain puzzling: after transformation strong positive correlations developed between choline and a group of five amino acids, whereas the same amino acids showed negative correlations with phosphocholine, a membrane phospholipid precursor. MMCA in conjunction with transcriptome analysis has opened a new window into the metabolome. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-015-0838-z) contains supplementary material, which is available to authorized users. Springer US 2015-08-11 2015 /pmc/articles/PMC4605990/ /pubmed/26491426 http://dx.doi.org/10.1007/s11306-015-0838-z Text en © The Author(s) 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Article Madhu, Basetti Narita, Masako Jauhiainen, Alexandra Menon, Suraj Stubbs, Marion Tavaré, Simon Narita, Masashi Griffiths, John R. Metabolomic changes during cellular transformation monitored by metabolite–metabolite correlation analysis and correlated with gene expression |
title | Metabolomic changes during cellular transformation monitored by metabolite–metabolite correlation analysis and correlated with gene expression |
title_full | Metabolomic changes during cellular transformation monitored by metabolite–metabolite correlation analysis and correlated with gene expression |
title_fullStr | Metabolomic changes during cellular transformation monitored by metabolite–metabolite correlation analysis and correlated with gene expression |
title_full_unstemmed | Metabolomic changes during cellular transformation monitored by metabolite–metabolite correlation analysis and correlated with gene expression |
title_short | Metabolomic changes during cellular transformation monitored by metabolite–metabolite correlation analysis and correlated with gene expression |
title_sort | metabolomic changes during cellular transformation monitored by metabolite–metabolite correlation analysis and correlated with gene expression |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4605990/ https://www.ncbi.nlm.nih.gov/pubmed/26491426 http://dx.doi.org/10.1007/s11306-015-0838-z |
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