Directed evolution of a genetic circuit

Abstract

The construction of artificial networks of transcriptional control elements in living cells represents a new frontier for biological engineering. However, biological circuit engineers will have to confront their inability to predict the precise behavior of even the most simple synthetic networks, a serious shortcoming and challenge for the design and construction of more sophisticated genetic circuitry in the future. We propose a combined rational and evolutionary design strategy for constructing genetic regulatory circuits, an approach that allows the engineer to fine-tune the biochemical parameters of the networks experimentally in vivo. By applying directed evolution to genes comprising a simple genetic circuit, we demonstrate that a nonfunctional circuit containing improperly matched components can evolve rapidly into a functional one. In the process, we generated a library of genetic devices with a range of behaviors that can be used to construct more complex circuits.

Fig 1.

The plasmid diagram shows the implementation of the present circuit. Plasmid pINV-110 constitutively expresses the LacI repressor, which inhibits transcription from the P_lac promoter in the absence of IPTG. The expression of the CI repressor and ECFP fluorescent marker is controlled by P_lac, which is inducible by externally added IPTG. Repressor CI acts on λP_RO12 on pINV-107b to repress the transcription of the EYFP gene, the output fluorescence indicator. The two plasmids contain different origins of replication as well as different antibiotic resistance genes, which allow them to be maintained stably within a single cell. The logic diagram (Upper Right) represents the logical representation of the same biochemical circuit. The P_lac promoter comprises an IMPLIES logic gate with respect to the two inputs LacI and IPTG and the output CI, whose truth table is shown below the diagram. The output of the IMPLIES gate, CI, is the input to the inverter based on the λP_RO12 promoter, ultimately controlling expression of the fluorescent output, EYFP. Note that the levels of EYFP output are the inverse of the input CI in the truth table. In this study, we targeted mutations to the CI protein.

Fig 2.

Switching characteristics of selected mutants. The output YFP levels were measured at 0.1 μM (LOW input, dark bars) and 1,000 μM IPTG (HIGH input, light bars). pINV-112-R3 is the rationally engineered mutant with an altered RBS. pINV-110 is the nonfunctional circuit used as the starting circuit for directed evolution.

Fig 3.

Transfer curves (output vs. input) of selected clones containing the genetic circuit. Dotted line: A4–04, solid line: C3, dashed line: pINV-112-R3. The curves were fitted to a Hill function: y = a/(1 + bxⁿ) + c, where x is IPTG concentration. The Hill coefficients n obtained are 1.7, 1.2, and 1.6 for A4–04, C3, and pINV-112-R3, respectively.

Fig 4.

The side chains of the mutated amino acid residues found in the evolved circuits are shown in the λ repressor CI tetramer-DNA model (Protein Data Bank ID code ). Mutated residues are shown in only one of the four repressor molecules. Summary of amino acid substitutions found in screened mutants (frequency in parentheses): I54F (11), K67N (7), V73I (18), E74D (1), E89D (1), Y103H (1), V105G (7), Q110L (1), R128G (1), W129R (1), T132A (2), E144G (7), V145A (1), A152S (1), P158A (1), L165F (1), D169A (1), E171G (1), F189V (1), V201A (1), F202V (11), Q204P (2), Q204R (1), Y210F (1), P214A (1), C215G (1), C215R (1), S220T (7), V221G (1), V221A (1), K224E (1), and E233G (7). Note that there are 10 mutants derived from A4 and six mutants from C3 that share common amino acid mutations with their respective parents.