Microbial carbon use efficiency predicted from genome-scale metabolic models.

Area of Science:

• Microbial ecology
• Biogeochemistry
• Computational biology

Background:

• Soil microbial respiration is a major global carbon flux.
• Understanding microbial metabolism controls is crucial for predicting carbon cycle responses to global change.

Purpose of the Study:

• To predict bacterial carbon-use efficiency (CUE) for over 200 species using computational metabolic modeling.
• To investigate the relationship between genome size, substrate access, and CUE in soil bacteria.
• To assess the impact of microbial physiological diversity on soil carbon cycling.

Main Methods:

• Genome-specific constraint-based metabolic modeling was employed in silico.
• Over 200 bacterial species' metabolic potential was analyzed.
• Phylogenetic structuring and correlations with genome size were examined.

Main Results:

• Potential bacterial CUE averages 0.62 ± 0.17, with a broad range (0.22–0.98).
• Phylogenetic structuring was observed at subphylum levels.
• Potential CUE negatively correlates with genome size; larger genomes grant access to more carbon substrates.

Conclusions:

• Interspecific variation in bacterial CUE is substantial and phylogenetically structured.
• Genome size influences carbon substrate utilization and CUE.
• Accounting for diverse microbial physiology is essential for accurate soil carbon cycle modeling and predicting global change impacts.