Quantifying absolute gene expression profiles reveals distinct regulation of central carbon metabolism genes in yeast

Abstract
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Abstract

In addition to controlled expression of genes by specific regulatory circuits, the abundance of proteins and transcripts can also be influenced by physiological states of the cell such as growth rate and metabolism. Here we examine the control of gene expression by growth rate and metabolism, by analyzing a multi-omics dataset consisting of absolute-quantitative abundances of the transcriptome, proteome, and amino acids in 22 steady-state yeast cultures. We find that transcription and translation are coordinately controlled by the cell growth rate via RNA polymerase II and ribosome abundance, but they are independently controlled by nitrogen metabolism via amino acid and nucleotide availabilities. Genes in central carbon metabolism, however, are distinctly regulated and do not respond to the cell growth rate or nitrogen metabolism as all other genes. Understanding these effects allows the confounding factors of growth rate and metabolism to be accounted for in gene expression profiling studies.

Data availability

Processed quantitative transcriptomics and proteomics data are in Supplementary Table 2 and 3. Processed intracellular amino acid concentrations are in Supplementary Table 4. Raw RNAseq data are available at ArrayExpress, accession E-MTAB-9117. The mass spectrometry proteomics data are deposited to the Proteome Xchange Consortium via the PRIDE partner repository with dataset identifier PXD021218.

The following data sets were generated

(2020) Quantification of global gene expression control by growth rate and metabolic cues
ArrayExpress, E-MTAB-9117.

http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-9117
1. E. Vorontsov
2. J. Nielsen
(2020) Quantifying gene expression control by growth and metabolism reveals distinct regulation of central carbon metabolism genes in yeast
PRIDE, PXD021218.

https://www.ebi.ac.uk/pride/archive/projects/PXD021218/

The following previously published data sets were used

(2019) Tanscriptome studies of yeast cell under a series of specific growth rates
NCBI BioProject, PRJNA523289.

https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA523289
(2019) Proteome studies of yeast cell under a series of specific growth rates
PRIDE, PXD012891.

https://www.ebi.ac.uk/pride/archive/projects/PXD012891/

Article and author information

Author details

Rosemary Yu

Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden

Competing interests
No competing interests declared.
Egor Vorontsov

Proteomics Core Facility, University of Gothenburg, Gothenburg, Sweden

Competing interests
No competing interests declared.
Carina Sihlbom

Proteomics core facility, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden

Competing interests
No competing interests declared.
Jens Nielsen

Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden

For correspondence
nielsenj@chalmers.se

Competing interests
Jens Nielsen, J.N. is the CEO of the BioInnovation Institute, Denmark..

"This ORCID iD identifies the author of this article:" 0000-0002-9955-6003

Funding

Novo Nordisk Fonden (NNF10CC1016517)

Rosemary Yu
Jens Nielsen

Knut och Alice Wallenbergs Stiftelse

Rosemary Yu
Jens Nielsen

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.