Carboxylic acids are an attractive biorenewable chemical. Enormous progress has been made in engineering microbes for production of these compounds though titers remain lower than desired. Here we used transcriptome analysis of Escherichia coli during exogenous challenge with octanoic acid (C8) at pH 7.0 to probe mechanisms of toxicity. This analysis highlights the intracellular acidification and membrane damage caused by C8 challenge. Network component analysis identified transcription factors with altered activity including GadE, the activator of the glutamate-dependent acid resistance system (AR2) and Lrp, the amino acid biosynthesis regulator. The intracellular acidification was quantified during exogenous challenge, but was not observed in a carboxylic acid producing strain, though this may be due to lower titers than those used in our exogenous challenge studies. We developed a framework for predicting the proton motive force during adaptation to strong inorganic acids and carboxylic acids. This model predicts that inorganic acid challenge is mitigated by cation accumulation, but that carboxylic acid challenge inverts the proton motive force and requires anion accumulation. Utilization of native acid resistance systems was not useful in terms of supporting growth or alleviating intracellular acidification. AR2 was found to be non-functional, possibly due to membrane damage. We proposed that interaction of Lrp and C8 resulted in repression of amino acid biosynthesis. However, this hypothesis was not supported by perturbation of lrp expression or amino acid supplementation. E. coli strains were also engineered for altered cyclopropane fatty acid content in the membrane, which had a dramatic effect on membrane properties, though C8 tolerance was not increased. We conclude that achieving higher production titers requires circumventing the membrane damage. As higher titers are achieved, acidification may become problematic.

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Currently, visualization tools for large ontologies (e.g., pathway and gene ontologies) result in a very flat wide tree that is difficult to fit on a single display. This paper develops the concept of using an enhanced radial space-filling (ERSF) layout to show biological ontologies efficiently. The ERSF technique represents ontology terms as circular regions in 3D. Orbital connections in a third dimension correspond to non-tree edges in the ontology that exist when an ontology term belongs to multiple categories. Biologists can use the ERSF layout to identify highly activated pathway or gene ontology categories by mapping experimental statistics such as coefficient of variation and overrepresentation values onto the visualization. This paper illustrates the use of the ERSF layout to explore pathway and gene ontologies using a gene expression dataset from E. coli.

Directed laboratory evolution is a common technique to obtain an evolved bacteria strain with a desired phenotype. This technique is especially useful as a supplement to rational engineering for complex phenotypes such as increased biocatalyst tolerance to toxic compounds. However, reverse engineering efforts are required in order to identify the mutations that occurred, including single nucleotide polymorphisms (SNPs), insertions/deletions (indels), duplications, and rearrangements. In this protocol, we describe the steps to (1) obtain and sequence the genomic DNA, (2) process and analyze the genomic DNA sequence data, and (3) verify the mutations by Sanger resequencing.

We characterize the equation of state for a simple three-dimensional DNA hairpin model using a Metropolis Monte Carlo algorithm. This algorithm was run at constant temperature and fixed separation between the terminal ends of the strand. From the equation of state, we compute the compressibility, thermal expansion coefficient, and specific heat along with adiabatic path.