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.
机构:
Univ Calif Berkeley, Dept Bioengn, Howard Hughes Med Inst, Berkeley, CA 94720 USAUniv Calif Berkeley, Dept Bioengn, Howard Hughes Med Inst, Berkeley, CA 94720 USA
Arkin, Adam P.
;
Fletcher, Daniel A.
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机构:Univ Calif Berkeley, Dept Bioengn, Howard Hughes Med Inst, Berkeley, CA 94720 USA
机构:
Univ Calif Berkeley, Dept Bioengn, Howard Hughes Med Inst, Berkeley, CA 94720 USAUniv Calif Berkeley, Dept Bioengn, Howard Hughes Med Inst, Berkeley, CA 94720 USA
Arkin, Adam P.
;
Fletcher, Daniel A.
论文数: 0引用数: 0
h-index: 0
机构:Univ Calif Berkeley, Dept Bioengn, Howard Hughes Med Inst, Berkeley, CA 94720 USA