Transcript level and sequence determinants of protein abundance and noise in Escherichia coli

Guimaraes, Joao C.; Rocha, Miguel; Arkin, Adam P.

doi:10.1093/nar/gku126

Transcript level and sequence determinants of protein abundance and noise in Escherichia coli

Journal Article · Thu Feb 06 00:00:00 EST 2014 · Nucleic Acids Research

DOI:https://doi.org/10.1093/nar/gku126· OSTI ID:1625533

Guimaraes, Joao C. ^[1]; Rocha, Miguel ^[2]; Arkin, Adam P. ^[3]

Univ. of California, Berkeley, CA (United States); Univ. of Minho, Braga (Portugal); DOE/OSTI
Univ. of Minho, Braga (Portugal)
Univ. of California, Berkeley, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

The range over which a protein is expressed, and its cell-to-cell variability, is often thought to be linked to the demand for its activity. Steady-state protein level is determined by multiple mechanisms controlling transcription and translation, many of which are limited by DNA- and RNA-encoded signals that affect initiation, elongation and termination of polymerases and ribosomes. We performed a comprehensive analysis of >100 sequence features to derive a predictive model composed of a minimal non-redundant set of factors explaining 66% of the total variation of protein abundance observed in >800 genes in Escherichia coli. The model suggests that protein abundance is primarily determined by the transcript level (53%) and by effectors of translation elongation (12%), whereas only a small fraction of the variation is explained by translational initiation (1%). Our analyses uncover a new sequence determinant, not previously described, affecting translation initiation and suggest that elongation rate is affected by both codon biases and specific amino acid composition. We also show that transcription and translation efficiency may have an effect on expression noise, which is more similar than previously assumed.

View Accepted Manuscript (DOE)

Research Organization:: Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1625533

Journal Information:: Nucleic Acids Research, Journal Name: Nucleic Acids Research Journal Issue: 8 Vol. 42; ISSN 0305-1048

Publisher:: Oxford University PressCopyright Statement

Country of Publication:: United States

Language:: English

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Transcriptome-guided parsimonious flux analysis improves predictions with metabolic networks in complex environments Jenior, Matthew L.; Moutinho, Thomas J.; Dougherty, Bonnie V. PLOS Computational Biology, Vol. 16, Issue 4 https://doi.org/10.1371/journal.pcbi.1007099	journal	April 2020
Multiplex methods provide effective integration of multi-omic data in genome-scale models Angione, Claudio; Conway, Max; Lio, Pietro Apollo - University of Cambridge Repository https://doi.org/10.17863/cam.4702	text	January 2016

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