Directed evolution of Escherichia coli with lower-than-natural plasmid mutation rates.

Unwanted evolution of designed DNA sequences limits metabolic and genome engineering efforts. Engineered functions that are burdensome to host cells and slow their replication are rapidly inactivated by mutations, and unplanned mutations with unpredictable effects often accumulate alongside designed changes in large-scale genome editing projects. We developed a directed evolution strategy, Periodic Reselection for Evolutionarily Reliable Variants (PResERV), to discover mutations that prolong the function of a burdensome DNA sequence in an engineered organism.

Innovation in an E. coli evolution experiment is contingent on maintaining adaptive potential until competition subsides.

Key innovations are disruptive evolutionary events that enable a species to escape constraints and rapidly diversify. After 15 years of the Lenski long-term evolution experiment with Escherichia coli, cells in one of the twelve populations evolved the ability to utilize citrate, an abundant but previously untapped carbon source in the environment. Descendants of these cells became dominant in the population and subsequently diversified as a consequence of invading this vacant niche.

Surveying the lipogenesis landscape in Yarrowia lipolytica through understanding the function of a Mga2p regulatory protein mutant.

Lipogenic organisms represent great starting points for metabolic engineering of oleochemical production. While previous engineering efforts were able to significantly improve lipid production in Yarrowia lipolytica, the lipogenesis landscape, especially with respect to regulatory elements, has not been fully explored. Through a comparative genomics and transcriptomics approach, we identified and validated a mutant mga2 protein that serves as a regulator of desaturase gene expression and potent lipogenesis factor.

Predicting the Genetic Stability of Engineered DNA Sequences with the EFM Calculator.

Unwanted evolution can rapidly degrade the performance of genetically engineered circuits and metabolic pathways installed in living organisms. We created the Evolutionary Failure Mode (EFM) Calculator to computationally detect common sources of genetic instability in an input DNA sequence. It predicts two types of mutational hotspots: deletions mediated by homologous recombination and indels caused by replication slippage on simple sequence repeats.

Genome instability mediates the loss of key traits by Acinetobacter baylyi ADP1 during laboratory evolution.

Acinetobacter baylyi ADP1 has the potential to be a versatile bacterial host for synthetic biology because it is naturally transformable. To examine the genetic reliability of this desirable trait and to understand the potential stability of other engineered capabilities, we propagated ADP1 for 1,000 generations of growth in rich nutrient broth and analyzed the genetic changes that evolved by whole-genome sequencing. Substantially reduced transformability and increased cellular aggregation evolved during the experiment.

Towards an informative mutant phenotype for every bacterial gene.

Mutant phenotypes provide strong clues to the functions of the underlying genes and could allow annotation of the millions of sequenced yet uncharacterized bacterial genes. However, it is not known how many genes have a phenotype under laboratory conditions, how many phenotypes are biologically interpretable for predicting gene function, and what experimental conditions are optimal to maximize the number of genes with a phenotype. To address these issues, we measured the mutant fitness of 1,586 genes of the ethanol-producing bacterium Zymomonas mobilis ZM4 across 492 diverse experiments and found statistically significant phenotypes for 89% of all assayed genes.

Dissecting a complex chemical stress: chemogenomic profiling of plant hydrolysates.

The efficient production of biofuels from cellulosic feedstocks will require the efficient fermentation of the sugars in hydrolyzed plant material. Unfortunately, plant hydrolysates also contain many compounds that inhibit microbial growth and fermentation. We used DNA-barcoded mutant libraries to identify genes that are important for hydrolysate tolerance in both Zymomonas mobilis (44 genes) and Saccharomyces cerevisiae (99 genes).