Relating microbial physiological performance to genome content

Background/Question/Methods

Plant polymer degradation is catalyzed by extracellular enzymes produced by microorganisms. Enzyme production is an enzyme-intensive process suggesting that it is tightly regulated and should be related to the ecological and evolutionary forces that shape the physiology and genome content of microorganisms. Microbial species vary in their ability to break down recalcitrant plant polymers, and therefore, we expect there exists a trade-off between microbial growth rates and extracellular enzyme production.

Our project goal is to identify functional signatures in the genomes of these microorganisms that characterize polymer degradation ability and examine whether the physiological performance is related to extracellular enzyme and transporter gene content of these microbes.

Thus, we conducted growth experiments to measure microbial activity for 15 fungal and bacterial model microorganisms.  First, we grew the microbes in sand microcosms with four different polymers as carbon source, and monitored polymer utilization by measuring respiration rate for 16 days.  Extracellular enzyme activity was then evaluated using fluorometric substrates, and biomass changes were measured by extraction and analysis of ergosterol on a high-pressure liquid chromatogram (HPLC) and via direct microscopy.  To test our hypotheses, we compared these physiological results to the genome content of the organisms. 

Results/Conclusions

The physiological data showed that there is correlation between respiration and fungal biomass changes, though the extent of change was not extensive.  Beta-glucosidase enzyme activity was also higher for growth on cellulose, xylose and polygalacturonic acid substrates.  We demonstrated that genetic signatures (Pfams, pathways, GO terms and orthologous groups) distinguish microorganisms by their ability to degrade different polymers. Thus, it is likely that these signatures can be used to predict respiration ability of other microorganisms.  Using similar approaches, we will test the efficacy of this predictive method for other microbial physiological mechanisms to determine how growth efficiency varies among organisms on different substrates.