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Metabolome-proteome differentiation coupled to microbial divergence.

ABSTRACT: Tandem high-throughput proteomics and metabolomics were employed to functionally characterize natural microbial biofilm communities. Distinct molecular signatures exist for each analyzed sample. Deconvolution of the high-resolution molecular data demonstrates that identified proteins and detected metabolites exhibit organism-specific correlation patterns. These patterns are reflective of the functional differentiation of two bacterial species that share the same genus and that co-occur in the sampled microbial communities. Our analyses indicate that the two species have similar niche breadths and are not in strong competition with one another.

SUBMITTER: Wilmes P

PROVIDER: S-EPMC2962434 | biostudies-literature | 2010 Oct

REPOSITORIES: biostudies-literature

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Metabolome-proteome differentiation coupled to microbial divergence.

Wilmes Paul P Bowen Benjamin P BP Thomas Brian C BC Mueller Ryan S RS Denef Vincent J VJ VerBerkmoes Nathan C NC Hettich Robert L RL Northen Trent R TR Banfield Jillian F JF

mBio 20101026 5

Tandem high-throughput proteomics and metabolomics were employed to functionally characterize natural microbial biofilm communities. Distinct molecular signatures exist for each analyzed sample. Deconvolution of the high-resolution molecular data demonstrates that identified proteins and detected metabolites exhibit organism-specific correlation patterns. These patterns are reflective of the functional differentiation of two bacterial species that share the same genus and that co-occur in the sa ...[more]

PMID: 20978538

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Project description:Determinations of thyrotropin (TSH) and free thyroxine (FT4) represent the gold standard in evaluation of thyroid function. To screen for novel peripheral biomarkers of thyroid function and to characterize FT4-associated physiological signatures in human plasma we used an untargeted OMICS approach in a thyrotoxicosis model.A sample of 16 healthy young men were treated with levothyroxine for 8 weeks and plasma was sampled before the intake was started as well as at two points during treatment and after its completion, respectively. Mass spectrometry-derived metabolite and protein levels were related to FT4 serum concentrations using mixed-effect linear regression models in a robust setting. To compile a molecular signature discriminating between thyrotoxicosis and euthyroidism, a random forest was trained and validated in a two-stage cross-validation procedure.Despite the absence of obvious clinical symptoms, mass spectrometry analyses detected 65 metabolites and 63 proteins exhibiting significant associations with serum FT4. A subset of 15 molecules allowed a robust and good prediction of thyroid hormone function (AUC?=?0.86) without prior information on TSH or FT4. Main FT4-associated signatures indicated increased resting energy expenditure, augmented defense against systemic oxidative stress, decreased lipoprotein particle levels, and increased levels of complement system proteins and coagulation factors. Further association findings question the reliability of kidney function assessment under hyperthyroid conditions and suggest a link between hyperthyroidism and cardiovascular diseases via increased dimethylarginine levels.Our results emphasize the power of untargeted OMICs approaches to detect novel pathways of thyroid hormone action. Furthermore, beyond TSH and FT4, we demonstrated the potential of such analyses to identify new molecular signatures for diagnosis and treatment of thyroid disorders. This study was registered at the German Clinical Trials Register (DRKS) [DRKS00011275] on the 16th of November 2016.

Dataset Information

Metabolome-proteome differentiation coupled to microbial divergence.

Publications

Metabolome-proteome differentiation coupled to microbial divergence.

Similar Datasets

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