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Genome-wide gene expression and RNA half-life measurements allow predictions of regulation and metabolic behavior in Methanosarcina acetivorans

Overview of attention for article published in BMC Genomics, November 2016
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Title
Genome-wide gene expression and RNA half-life measurements allow predictions of regulation and metabolic behavior in Methanosarcina acetivorans
Published in
BMC Genomics, November 2016
DOI 10.1186/s12864-016-3219-8
Pubmed ID
Authors

Joseph R. Peterson, ShengShee Thor, Lars Kohler, Petra R.A. Kohler, William W. Metcalf, Zaida Luthey-Schulten

Abstract

While a few studies on the variations in mRNA expression and half-lives measured under different growth conditions have been used to predict patterns of regulation in bacterial organisms, the extent to which this information can also play a role in defining metabolic phenotypes has yet to be examined systematically. Here we present the first comprehensive study for a model methanogen. We use expression and half-life data for the methanogen Methanosarcina acetivorans growing on fast- and slow-growth substrates to examine the regulation of its genes. Unlike Escherichia coli where only small shifts in half-lives were observed, we found that most mRNA have significantly longer half-lives for slow growth on acetate compared to fast growth on methanol or trimethylamine. Interestingly, half-life shifts are not uniform across functional classes of enzymes, suggesting the existence of a selective stabilization mechanism for mRNAs. Using the transcriptomics data we determined whether transcription or degradation rate controls the change in transcript abundance. Degradation was found to control abundance for about half of the metabolic genes underscoring its role in regulating metabolism. Genes involved in half of the metabolic reactions were found to be differentially expressed among the substrates suggesting the existence of drastically different metabolic phenotypes that extend beyond just the methanogenesis pathways. By integrating expression data with an updated metabolic model of the organism (iST807) significant differences in pathway flux and production of metabolites were predicted for the three growth substrates. This study provides the first global picture of differential expression and half-lives for a class II methanogen, as well as provides the first evidence in a single organism that drastic genome-wide shifts in RNA half-lives can be modulated by growth substrate. We determined which genes in each metabolic pathway control the flux and classified them as regulated by transcription (e.g. transcription factor) or degradation (e.g. post-transcriptional modification). We found that more than half of genes in metabolism were controlled by degradation. Our results suggest that M. acetivorans employs extensive post-transcriptional regulation to optimize key metabolic steps, and more generally that degradation could play a much greater role in optimizing an organism's metabolism than previously thought.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
Unknown 58 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 17%
Student > Master 10 17%
Researcher 8 14%
Student > Bachelor 6 10%
Professor > Associate Professor 4 7%
Other 8 14%
Unknown 13 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 16 27%
Agricultural and Biological Sciences 13 22%
Chemistry 3 5%
Computer Science 2 3%
Environmental Science 2 3%
Other 10 17%
Unknown 13 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 09 September 2017.
All research outputs
#16,982,449
of 25,734,859 outputs
Outputs from BMC Genomics
#6,635
of 11,314 outputs
Outputs of similar age
#178,125
of 289,104 outputs
Outputs of similar age from BMC Genomics
#114
of 220 outputs
Altmetric has tracked 25,734,859 research outputs across all sources so far. This one is in the 31st percentile – i.e., 31% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,314 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 36th percentile – i.e., 36% of its peers scored the same or lower than it.
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