Mass spectrometry of the M. smegmatis proteome: Protein expression levels correlate with function, operons, and codon bias
Open Access
- 2 August 2005
- journal article
- Published by Cold Spring Harbor Laboratory in Genome Research
- Vol. 15 (8) , 1118-1126
- https://doi.org/10.1101/gr.3994105
Abstract
The fast-growing bacterium Mycobacterium smegmatis is a model mycobacterial system, a nonpathogenic soil bacterium that nonetheless shares many features with the pathogenic Mycobacterium tuberculosis, the causative agent of tuberculosis. The study of M. smegmatis is expected to shed light on mechanisms of mycobacterial growth and complex lipid metabolism, and provides a tractable system for antimycobacterial drug development. Although the M. smegmatis genome sequence is not yet completed, we used multidimensional chromatography and tandem mass spectrometry, in combination with the partially completed genome sequence, to detect and identify a total of 901 distinct proteins from M. smegmatis over the course of 25 growth conditions, providing experimental annotation for many predicted genes with an ∼5% false-positive identification rate. We observed numerous proteins involved in energy production (9.8% of expressed proteins), protein translation (8.7%), and lipid biosynthesis (5.4%); 33% of the 901 proteins are of unknown function. Protein expression levels were estimated from the number of observations of each protein, allowing measurement of differential expression of complete operons, and the comparison of the stationary and exponential phase proteomes. Expression levels are correlated with proteins' codon biases and mRNA expression levels, as measured by comparison with codon adaptation indices, principle component analysis of codon frequencies, and DNA microarray data. This observation is consistent with notions that either (1) prokaryotic protein expression levels are largely preset by codon choice, or (2) codon choice is optimized for consistency with average expression levels regardless of the mechanism of regulating expression.Keywords
This publication has 45 references indexed in Scilit:
- Integrating high-throughput and computational data elucidates bacterial networksNature, 2004
- Proteogenomic mapping as a complementary method to perform genome annotationProteomics, 2004
- SigM, an Extracytoplasmic Function Sigma Factor ofBacillus subtilis, Is Activated in Response to Cell Wall Antibiotics, Ethanol, Heat, Acid, and Superoxide StressJournal of Bacteriology, 2003
- Mass spectrometry-based proteomicsNature, 2003
- Functional Modulation of Escherichia Coli RNA PolymeraseAnnual Review of Microbiology, 2000
- Identification and transcriptional characterization of the gene encoding the stress-response σ factor σHinStreptomyces coelicolorA3(2)FEMS Microbiology Letters, 2000
- Probability-based protein identification by searching sequence databases using mass spectrometry dataElectrophoresis, 1999
- Improved microbial gene identification with GLIMMERNucleic Acids Research, 1999
- Deciphering the biology of Mycobacterium tuberculosis from the complete genome sequenceNature, 1998
- An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein databaseJournal of the American Society for Mass Spectrometry, 1994