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  4. Transcriptome and Proteome Dynamics of a Light-Dark Synchronized Bacterial Cell Cycle

Transcriptome and Proteome Dynamics of a Light-Dark Synchronized Bacterial Cell Cycle

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Author(s)
Chisholm, Sallie (Penny)
•
Waldbauer, Jacob R.
•
Rodrigue, Sébastien
•
Coleman, Maureen L
Date Issued
August 2012
Journal
PLoS ONE
Publisher
Public Library of Science
Citation
Waldbauer, Jacob R. et al. “Transcriptome and Proteome Dynamics of a Light-Dark Synchronized Bacterial Cell Cycle.” Ed. Senjie Lin. PLoS ONE 7.8 (2012).
Version
Final published version
Abstract
Growth of the ocean's most abundant primary producer, the cyanobacterium Prochlorococcus, is tightly synchronized to the natural 24-hour light-dark cycle. We sought to quantify the relationship between transcriptome and proteome dynamics that underlie this obligate photoautotroph's highly choreographed response to the daily oscillation in energy supply. Using RNA-sequencing transcriptomics and mass spectrometry-based quantitative proteomics, we measured timecourses of paired mRNA-protein abundances for 312 genes every 2 hours over a light-dark cycle. These temporal expression patterns reveal strong oscillations in transcript abundance that are broadly damped at the protein level, with mRNA levels varying on average 2.3 times more than the corresponding protein. The single strongest observed protein-level oscillation is in a ribonucleotide reductase, which may reflect a defense strategy against phage infection. The peak in abundance of most proteins also lags that of their transcript by 2–8 hours, and the two are completely antiphase for some genes. While abundant antisense RNA was detected, it apparently does not account for the observed divergences between expression levels. The redirection of flux through central carbon metabolism from daytime carbon fixation to nighttime respiration is associated with quite small changes in relative enzyme abundances. Our results indicate that expression responses to periodic stimuli that are common in natural ecosystems (such as the diel cycle) can diverge significantly between the mRNA and protein levels. Protein expression patterns that are distinct from those of cognate mRNA have implications for the interpretation of transcriptome and metatranscriptome data in terms of cellular metabolism and its biogeochemical impact.
MIT Department
Massachusetts Institute of Technology. Department of Biology
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
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Creative Commons Attribution
http://creativecommons.org/licenses/by/2.5/
Persistent DSpace Link
http://hdl.handle.net/1721.1/74633
DOI of Published Version
https://doi.org/10.1371/journal.pone.0043432
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