Comparing expression level-dependent features in codon usage with protein abundance: An analysis of 'predictive proteomics'

McHardy AC, Pühler A, Kalinowski J, Meyer F (2004)
PROTEOMICS 4(1): 46-58.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
Download
Es wurden keine Dateien hochgeladen. Nur Publikationsnachweis!
Autor*in
Abstract / Bemerkung
Synonymous codon usage is a commonly used means for estimating gene expression levels of Escherichia coli genes and has also been used for predicting highly expressed genes for a number of prokaryotic genomes. By comparison of expression level-dependent features in codon usage with protein abundance data from two proteome studies of exponentially growing E. coli and Bacillus subtilis cells, we try to evaluate whether the implicit assumption of this approach can be confirmed with experimental data. Log-odds ratio scores are used to model differences in codon usage between highly expressed genes and genomic average. Using these, the strength and significance of expression level-dependent features in codon usage were determined for the genes of the Escherichia coli, Bacillus subtilis and Haemophilus influenzae genomes. The comparison of codon usage features with protein abundance data confirmed a relationship between these to be present, although exceptions to this, possibly related to functional context, were found. For species with expression level-dependent features in their codon usage, the applied methodology could be used to improve in silico simulations of the outcome of two-dimensional gel electrophoretic experiments.
Stichworte
expression level; codon adaptation index; codon usage; two-dimensional gel electrophoresis; protein abundance; synonymous
Erscheinungsjahr
2004
Zeitschriftentitel
PROTEOMICS
Band
4
Ausgabe
1
Seite(n)
46-58
ISSN
1615-9853
eISSN
1615-9861
Page URI
https://pub.uni-bielefeld.de/record/1608839

Zitieren

McHardy AC, Pühler A, Kalinowski J, Meyer F. Comparing expression level-dependent features in codon usage with protein abundance: An analysis of 'predictive proteomics'. PROTEOMICS. 2004;4(1):46-58.
McHardy, A. C., Pühler, A., Kalinowski, J., & Meyer, F. (2004). Comparing expression level-dependent features in codon usage with protein abundance: An analysis of 'predictive proteomics'. PROTEOMICS, 4(1), 46-58. https://doi.org/10.1002/pmic.200300501
McHardy, AC, Pühler, Alfred, Kalinowski, Jörn, and Meyer, F. 2004. “Comparing expression level-dependent features in codon usage with protein abundance: An analysis of 'predictive proteomics'”. PROTEOMICS 4 (1): 46-58.
McHardy, A. C., Pühler, A., Kalinowski, J., and Meyer, F. (2004). Comparing expression level-dependent features in codon usage with protein abundance: An analysis of 'predictive proteomics'. PROTEOMICS 4, 46-58.
McHardy, A.C., et al., 2004. Comparing expression level-dependent features in codon usage with protein abundance: An analysis of 'predictive proteomics'. PROTEOMICS, 4(1), p 46-58.
A.C. McHardy, et al., “Comparing expression level-dependent features in codon usage with protein abundance: An analysis of 'predictive proteomics'”, PROTEOMICS, vol. 4, 2004, pp. 46-58.
McHardy, A.C., Pühler, A., Kalinowski, J., Meyer, F.: Comparing expression level-dependent features in codon usage with protein abundance: An analysis of 'predictive proteomics'. PROTEOMICS. 4, 46-58 (2004).
McHardy, AC, Pühler, Alfred, Kalinowski, Jörn, and Meyer, F. “Comparing expression level-dependent features in codon usage with protein abundance: An analysis of 'predictive proteomics'”. PROTEOMICS 4.1 (2004): 46-58.

12 Zitationen in Europe PMC

Daten bereitgestellt von Europe PubMed Central.

De novo transcriptome sequencing and sequence analysis of the malaria vector Anopheles sinensis (Diptera: Culicidae).
Chen B, Zhang YJ, He Z, Li W, Si F, Tang Y, He Q, Qiao L, Yan Z, Fu W, Che Y., Parasit Vectors 7(), 2014
PMID: 25000941
Automated isolation of translational efficiency bias that resists the confounding effect of GC(AT)-content.
Raiford DW, Krane DE, Doom TE, Raymer ML., IEEE/ACM Trans Comput Biol Bioinform 7(2), 2010
PMID: 20431144
A probabilistic framework to improve microrna target prediction by incorporating proteomics data.
Li J, Min R, Bonner A, Zhang Z., J Bioinform Comput Biol 7(6), 2009
PMID: 20014473
The effects of differential gene expression on coding sequence features: analysis by one-way ANOVA.
Wu G, Nie L, Freeland SJ., Biochem Biophys Res Commun 358(4), 2007
PMID: 17517370
The Escherichia coli proteome: past, present, and future prospects.
Han MJ, Lee SY., Microbiol Mol Biol Rev 70(2), 2006
PMID: 16760308
Amino acid cost and codon-usage biases in 6 prokaryotic genomes: a whole-genome analysis.
Heizer EM, Raiford DW, Raymer ML, Doom TE, Miller RV, Krane DE., Mol Biol Evol 23(9), 2006
PMID: 16754641
Comparative context analysis of codon pairs on an ORFeome scale.
Moura G, Pinheiro M, Silva R, Miranda I, Afreixo V, Dias G, Freitas A, Oliveira JL, Santos MA., Genome Biol 6(3), 2005
PMID: 15774029
Classification of hyper-variable Corynebacterium glutamicum surface-layer proteins by sequence analyses and atomic force microscopy.
Hansmeier N, Bartels FW, Ros R, Anselmetti D, Tauch A, Pühler A, Kalinowski J., J Biotechnol 112(1-2), 2004
PMID: 15288952
Export

Markieren/ Markierung löschen
Markierte Publikationen

Open Data PUB

Web of Science

Dieser Datensatz im Web of Science®
Quellen

PMID: 14730671
PubMed | Europe PMC

Suchen in

Google Scholar