An Orthogonal Multi-input Integration System to Control Gene Expression in Escherichia coli

Abstract

In many biotechnological applications, it is useful for gene expression to be regulated by multiple signals, as this allows the programming of complex behavior. Here we implement, in Escherichia coli, a system that compares the concentration of two signal molecules, and tunes GFP expression proportionally to their relative abundance. The computation is performed via molecular titration between an orthogonal σ factor and its cognate anti-σ factor. We use mathematical modeling and experiments to show that the computation system is predictable and able to adapt GFP expression dynamically to a wide range of combinations of the two signals, and our model qualitatively captures most of these behaviors. We also demonstrate in silico the practical applicability of the system as a reference-comparator, which compares an intrinsic signal (reflecting the state of the system) with an extrinsic signal (reflecting the desired reference state) in a multicellular feedback control strategy.

Multicellular feedback control of a genetic toggle-switch in microbial consortia

“…The in-vivo implementation of the consortium we propose is currently beyond what is technologically possible but is not unrealistic given that each of the controller population is similar to the reference comparator that was implemented experimentally in [18] and the antithetic feedback controller recently presented in [19]. Also, orthogonal communication channels able to set in place the required interaction between α 0…”

Ultrasensitive molecular controllers for quasi-integral feedback

“…3 and Table 1). As several other reaction networks for closed-loop control [15,16,14,18], the Brink motif relies on sequestration, which is expected to yield a high inputoutput gain. There is evidence that this mechanism can also produce integral action [11,12], however only in the ideal condition of fast sequestration and negligible degradation/dilution rates [19]; the latter requirement may be difficult to achieve in living cells.…”

“…Recent theoretical work has explored the use of molecular sequestration to build molecular controllers that perform integral action [11]. Ongoing experimental research aims at building sequestration-based integral controllers using sigma and anti-sigma factors in E. coli [12]; this research builds on ample evidence that sequestration is suited to achieve concentration reference tracking, with implementations that go beyond sigma and anti-sigma factors [13,14] and range from nucleic acid networks in vitro [15], to protein [16] and RNA-based sequestration [17,18]. A significant challenge in implementing integral action with sequestration alone is posed by the presence of dilu-tion, which introduces steady-state error (leaky integration) [19].…”

Hard Limits and Performance Tradeoffs in a Class of Sequestration Feedback Systems

“…An endogenous biological system that uses sequestration feedback to achieve perfect adaptation relies on the binding of sigma factor σ 70 to anti-sigma factor Rsd [27]. Examples of synthetic biological systems that employ sequestration feedback include a concentration tracker [28,29], two bacterial cell growth controllers [30], and a gene expression controller [31].…”