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Measurement of Specific Mycobacterial Mistranslation Rates with Gain-of-function Reporter Systems

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Metabolic and translational efficiency in microbial organisms.

Douglas W Raiford¹, Esley M Heizer, Robert V Miller

¹Department of Computer Science, University of Montana, Missoula, MT, USA. douglas.raiford@umontana.edu

Journal of Molecular Evolution

|April 28, 2012

Summary

Metabolic efficiency shapes microbial proteomes by favoring less expensive amino acids in highly expressed proteins. This study analyzed 1,700 genomes, finding 389 exhibit strong translational efficiency bias.

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Area of Science:

Microbial genomics
Proteomics
Biochemistry

Background:

Metabolic efficiency is a known selective force in some microbes.
Previous studies used proxies like molecular weight and overlooked lifestyle or auxotrophy.
Extensive analysis across diverse microbial life is needed.

Purpose of the Study:

To investigate metabolic efficiency as a driver of proteome evolution across all sequenced microbial organisms.
To refine the assessment of protein production costs by incorporating lifestyle-specific amino acid biosynthesis and auxotrophy.
To identify organisms exhibiting significant translational efficiency bias.

Main Methods:

Analysis of lifestyle-specific amino acid biosynthesis pathways to determine protein production costs.
Compensation for auxotrophy in cost calculations.
Utilizing codon usage bias as a proxy for protein expressivity.
Comprehensive analysis of 1,700 sequenced microbial genomes.

Main Results:

Identified a tendency for highly expressed proteins to use less biosynthetically expensive amino acids, indicating cost selection.
389 out of 1,700 sequenced organisms showed strong translational efficiency bias.
Lifestyle and auxotrophy were successfully integrated into cost analysis.

Conclusions:

Metabolic efficiency significantly influences proteome composition across a wide range of microbial life.
Translational efficiency bias is a common, yet previously underappreciated, evolutionary strategy in microbes.
This study provides a more accurate and comprehensive understanding of metabolic cost selection in microbial evolution.