Lactobacillus casei as a biocatalyst for biofuel production.

Microbial fermentation of sugars from plant biomass to alcohols represents an alternative to petroleum-based fuels. The optimal biocatalyst for such fermentations needs to overcome hurdles such as high concentrations of alcohols and toxic compounds. Lactic acid bacteria, especially lactobacilli, have high innate alcohol tolerance and are remarkably adaptive to harsh environments. This study assessed the potential of five Lactobacillus casei strains as biocatalysts for alcohol production. L. casei 12A was selected based upon its innate alcohol tolerance, high transformation efficiency and ability to utilize plant-derived carbohydrates. A 12A derivative engineered to produce ethanol (L. casei E1) was compared to two other bacterial biocatalysts. Maximal growth rate, maximal optical density and ethanol production were determined under conditions similar to those present during alcohol production from lignocellulosic feedstocks. L. casei E1 exhibited higher innate alcohol tolerance, better growth in the presence of corn stover hydrolysate stressors, and resulted in higher ethanol yields.

Genome-scale reconstruction of metabolic networks of Lactobacillus casei ATCC 334 and 12A.

Lactobacillus casei strains are widely used in industry and the utility of this organism in these industrial applications is strain dependent. Hence, tools capable of predicting strain specific phenotypes would have utility in the selection of strains for specific industrial processes. Genome-scale metabolic models can be utilized to better understand genotype-phenotype relationships and to compare different organisms. To assist in the selection and development of strains with enhanced industrial utility, genome-scale models for L. casei ATCC 334, a well characterized strain, and strain 12A, a corn silage isolate, were constructed. Draft models were generated from RAST genome annotations using the Model SEED database and refined by evaluating ATP generating cycles, mass-and-charge-balances of reactions, and growth phenotypes. After the validation process was finished, we compared the metabolic networks of these two strains to identify metabolic, genetic and ortholog differences that may lead to different phenotypic behaviors. We conclude that the metabolic capabilities of the two networks are highly similar. The L. casei ATCC 334 model accounts for 1,040 reactions, 959 metabolites and 548 genes, while the L. casei 12A model accounts for 1,076 reactions, 979 metabolites and 640 genes. The developed L. casei ATCC 334 and 12A metabolic models will enable better understanding of the physiology of these organisms and be valuable tools in the development and selection of strains with enhanced utility in a variety of industrial applications.

Evaluation of NaCl, pH, and lactic acid on the growth of Shiga toxin-producing Escherichia coli in a liquid Cheddar cheese extract.

A Cheddar cheese model system, Cheddar cheese extract, was used to examine how different levels of known microbial hurdles (NaCl, pH, and lactic acid) in Cheddar cheese contribute to inhibition of bacterial pathogens. This knowledge is critical to evaluate the safety of Cheddar varieties with altered compositions. The range of levels used covered the lowest and highest level of these factors present in low-sodium, low-fat, and traditional Cheddar cheeses. Four pathogens were examined in this model system at 11 °C for 6 wk, with the lowest levels of these inhibitory factors that would be encountered in these products. The 4 pathogens examined were Salmonella enterica, Staphylococcus aureus, Listeria monocytogenes, and Shiga toxin-producing Escherichia coli (STEC). None of these organisms were capable of growth under these conditions. The STEC exhibited the highest survival and hence was used to examine which of these inhibitory factors (NaCl, pH, and lactic acid) was primarily responsible for the observed inhibition. The STEC survival was examined in Cheddar cheese extract varying in NaCl (1.2 vs. 4.8%), lactic acid (2.7 vs. 4.3%), and pH (4.8 vs. 5.3) at 11 °C for 6 wk. The microbial hurdle found to have the greatest effect on STEC survival was pH. The interactions between pH and levels of protonated lactic acid and anionic lactic acid with STEC survival was also evaluated; only the concentration of protonated lactic acid was determined to have a significant effect on STEC survival. These results indicate that, of the pathogens examined, STEC is of the greatest concern in Cheddar varieties with altered compositions and that pH is the microbial hurdle primarily responsible for controlling STEC in these products.