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

Abstract

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.

Programming Escherichia coli to function as a digital display

“…design, it would be impactful to genetic engineering projects if there were simple metrics of resource utilization assigned to parts and devices that could be used to predict the stability of a synthetic genetic system prior to it being constructed (Jack et al, 2015). Implementing the BCD converter required balancing many regulatory proteins such they dynamically work together as a network to perform the desired function.…”

Integrase-mediated differentiation circuits improve evolutionary stability of burdensome and toxic functions in E. coli

“…At the level of sequence design, minimizing repeated sequences and parts diminishes mutations due to homologous recombination (HR) and improves circuit half-life, 2 and researchers may evaluate sequences in silico for such HR and repeat-mediated mutations with the EFM calculator. 4 Alternatively, strains have been engineered to globally reduce mutation rates by disrupting the cell's capacity for HR with recA knockout, knocking out error-prone polymerases to reduce point mutations, and removing selfish transposon elements that otherwise may insert themselves and disrupt circuit function. [5][6][7] Though such strategies may delay the acquisition of destructive mutations, other approaches are necessary to impact the rate at which mutations are selected in the population.…”

CRISPR-interference based modulation of mobile genetic elements in bacteria

“…Several strategies are already available to deal with this issue (2,3): One possibility is to engineer redundant genetic circuits that can withstand mutations without loss-offunction (4). Another solution is to design DNA sequences that are less prone to mutation-acquisition, mainly by relying on experimental observations and computational designs (5,6). Yet another way to limit the evolution of genes of interest is to link their expression to that of an essential gene (6,7).…”