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. Mutations responsible for the appearance of rudimentary citrate utilization and for refining this ability have been characterized. However, the complete nature of the genetic and/or ecological events that set the stage for this key innovation is unknown. In particular, it is unclear why it took so long for citrate utilization to evolve and why it still has evolved in only one of the twelve E. coli populations after 30 years of the Lenski experiment. In this study, we recapitulated the initial mutation needed to evolve citrate utilization in strains isolated from throughout the first 31,500 generations of the history of this population. We found that there was already a slight fitness benefit for this mutation in the original ancestor of the evolution experiment and in other early isolates. However, evolution of citrate utilization was blocked at this point due to competition with other mutations that improved fitness in the original niche. Subsequently, an anti-potentiated genetic background evolved in which it was deleterious to evolve rudimentary citrate utilization. Only later, after further mutations accumulated that restored the benefit of this first-step mutation and the overall rate of adaptation in the population slowed, was citrate utilization likely to evolve. Thus, intense competition and the types of mutations that it favors can lead to short-sighted evolutionary trajectories that hide a stepping stone needed to access a key innovation from many future generations.

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. Here, we used PResERV to isolate Escherichia coli cells that replicate ColE1-type plasmids with higher fidelity. We found mutations in DNA polymerase I and in RNase E that reduce plasmid mutation rates by 6- to 30-fold. The PResERV method implicitly selects to maintain the growth rate of host cells, and high plasmid copy numbers and gene expression levels are maintained in some of the evolved E. coli strains, indicating that it is possible to improve the genetic stability of cellular chassis without encountering trade-offs in other desirable performance characteristics. Utilizing these new antimutator E. coli and applying PResERV to other organisms in the future promises to prevent evolutionary failures and unpredictability to provide a more stable genetic foundation for synthetic biology.

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. New insertions of IS1236 transposable elements and IS1236-mediated deletions led to these phenotypes in most cases and were common overall among the selected mutations. We also observed a 49-kb deletion of a prophage region that removed an integration site, which has been used for genome engineering, from every evolved genome. The comparatively low rates of these three classes of mutations in lineages that were propagated with reduced selection for 7,500 generations indicate that they increase ADP1 fitness under common laboratory growth conditions. Our results suggest that eliminating transposable elements and other genetic failure modes that affect key organismal traits is essential for improving the reliability of metabolic engineering and genome editing in undomesticated microbial hosts, such as Acinetobacter baylyi ADP1.

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. The resulting strain is enriched in unsaturated fatty acids. Comparing the underlying mechanism of this mutant to other previously engineered strains suggests that creating an imbalance between glycolysis and the TCA cycle can serve as a driving force for lipogenesis when combined with fatty acid catabolism overexpressions. Further comparative transcriptomics analysis revealed both distinct and convergent rewiring associated with these different genotypes. Finally, by combining metabolic engineering targets, it is possible to further engineer a strain containing the mutant mga2 gene to a lipid production titer of 25g/L.

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. Thus, in Z. mobilis, most genes have a functional consequence under laboratory conditions. We demonstrate that 41% of Z. mobilis genes have both a strong phenotype and a similar fitness pattern (cofitness) to another gene, and are therefore good candidates for functional annotation using mutant fitness. Among 502 poorly characterized Z. mobilis genes, we identified a significant cofitness relationship for 174. For 57 of these genes without a specific functional annotation, we found additional evidence to support the biological significance of these gene-gene associations, and in 33 instances, we were able to predict specific physiological or biochemical roles for the poorly characterized genes. Last, we identified a set of 79 diverse mutant fitness experiments in Z. mobilis that are nearly as biologically informative as the entire set of 492 experiments. Therefore, our work provides a blueprint for the functional annotation of diverse bacteria using mutant fitness.

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). Overexpression of a Z. mobilis tolerance gene of unknown function (ZMO1875) improved its specific ethanol productivity 2.4-fold in the presence of miscanthus hydrolysate. However, a mixture of 37 hydrolysate-derived inhibitors was not sufficient to explain the fitness profile of plant hydrolysate. To deconstruct the fitness profile of hydrolysate, we profiled the 37 inhibitors against a library of Z. mobilis mutants and we modeled fitness in hydrolysate as a mixture of fitness in its components. By examining outliers in this model, we identified methylglyoxal as a previously unknown component of hydrolysate. Our work provides a general strategy to dissect how microbes respond to a complex chemical stress and should enable further engineering of hydrolysate tolerance.

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. We tested the performance of our algorithm on genetic circuits that were previously redesigned for greater evolutionary reliability and analyzed the stability of sequences in the iGEM Registry of Standard Biological Parts. More than half of the parts in the Registry are predicted to experience >100-fold elevated mutation rates due to the inclusion of unstable sequence configurations. We anticipate that the EFM Calculator will be a useful negative design tool for avoiding volatile DNA encodings, thereby increasing the evolutionary lifetimes of synthetic biology devices.