PLoS ONE (Jan 2011)
Transcriptional analysis of Lactobacillus brevis to N-butanol and ferulic acid stress responses.
Abstract
BackgroundThe presence of anti-microbial phenolic compounds, such as the model compound ferulic acid, in biomass hydrolysates pose significant challenges to the widespread use of biomass in conjunction with whole cell biocatalysis or fermentation. Currently, these inhibitory compounds must be removed through additional downstream processing or sufficiently diluted to create environments suitable for most industrially important microbial strains. Simultaneously, product toxicity must also be overcome to allow for efficient production of next generation biofuels such as n-butanol, isopropanol, and others from these low cost feedstocks.Methodology and principal findingsThis study explores the high ferulic acid and n-butanol tolerance in Lactobacillus brevis, a lactic acid bacterium often found in fermentation processes, by global transcriptional response analysis. The transcriptional profile of L. brevis reveals that the presence of ferulic acid triggers the expression of currently uncharacterized membrane proteins, possibly in an effort to counteract ferulic acid induced changes in membrane fluidity and ion leakage. In contrast to the ferulic acid stress response, n-butanol challenges to growing cultures primarily induce genes within the fatty acid synthesis pathway and reduced the proportion of 19:1 cyclopropane fatty acid within the L. brevis membrane. Both inhibitors also triggered generalized stress responses. Separate attempts to alter flux through the Escherichia coli fatty acid synthesis by overexpressing acetyl-CoA carboxylase subunits and deleting cyclopropane fatty acid synthase (cfa) both failed to improve n-butanol tolerance in E. coli, indicating that additional components of the stress response are required to confer n-butanol resistance.ConclusionsSeveral promising routes for understanding both ferulic acid and n-butanol tolerance have been identified from L. brevis gene expression data. These insights may be used to guide further engineering of model industrial organisms to better tolerate both classes of inhibitors to enable facile production of biofuels from lignocellulosic biomass.