Feedforward Loops: Evolutionary Conserved Network Motifs Redesigned for Synthetic Biology Applications

Abstract

Feedforward loops (FFLs) are relatively simple network motifs, made of three interacting genes, that have been found in a large number in E. coli and S. cerevisiae. More recently, they have also been discovered in multicellular eukaryotes. FFLs are evolutionary favored motifs because they enable cells to survive critical environmental conditions. Among the eight types of possible FFLs, the so-called coherent 1 and incoherent 1 FFL are the most abundant. The former carries out a sign-sensitive delay in gene expression; the latter is a pulse generator and a response time accelerator. So far, only few synthetic FFLs have been engineered, either in cell-free systems or in vivo. In this work, we review the main experimental works published on FFLs, with particular focus on novel designs for synthetic FFLs. They are, indeed, quite different from the natural ones that arose during the course of evolution.

Design and Model-Driven Analysis of Synthetic Circuits with the Staphylococcus aureus Dead-Cas9 (sadCas9) as a Programmable Transcriptional Regulator in Bacteria

“…To evaluate the CRISPRi/sadCas9 system in the design of more complex networks, with both static and dynamic behaviors, we constructed type-1 incoherent feedforward loop (iFFL) circuits, often used as a testbed for synthetic biological functions. The iFFL architecture is a network motif commonly found in nature and exploited in synthetic biology for engineering a number of dynamic (e.g., pulse generation, response time accelerator) and static functionalities (pattern formation, stabilization of gene expression). , Depending on the used components, the dynamic behavior of the output is expected to show a pulse-like or a monotonically increasing trend over time, eventually reaching a steady-state fluorescence level . Regarding the steady-state output, a typical and well-known response is the bell-shaped curve as a function of the input concentration, used to generate patterns of gene expression, e.g., band-pass filters or French flag stripe patterning. , Another previously reported response of iFFL is a sigmoidal dose–response curve, when the circuit was designed for stabilizing gene expression, e.g., to counteract copy number changes, and it was important to obtain a constant steady-state output for wide ranges of input concentrations .…”

“…The iFFL architecture is a network motif commonly found in nature and exploited in synthetic biology for engineering a number of dynamic (e.g., pulse generation, response time accelerator) and static functionalities (pattern formation, stabilization of gene expression). 56,57 Depending on the used components, the dynamic behavior of the output is expected to show a pulse-like or a monotonically increasing trend over time, eventually reaching a steady-state fluorescence level. 58 Regarding the steady-state output, a typical and wellknown response is the bell-shaped curve as a function of the input concentration, used to generate patterns of gene expression, e.g., band-pass filters or French flag stripe patterning.…”

Florigen-producing cells express FPF1-LIKE PROTEIN 1 that accelerates flowering and stem growth in long days with sunlight red/far-red ratio inArabidopsis

“…The C1-FFL is the most common feed-forward loops that exist in biological systems, and the OR logic C1-FFL ensures continuous output generation (i.e., continuous flowering induction) even having an abrupt loss of input signals (i.e., variable nature of flowering inducing environmental conditions). 51,52 Having the FT/FLP1 C1-FFL may facilitate plants to induce and maintain flowering status under ever-changing natural environments in spring.…”

Association between gene expression plasticity and regulatory network topology

“…Two studies on synthetic bacteria (Basu et al ., 2004) and Escherichia coli (Sen et al ., 2014) brought experimental evidence of a link between feedforward loops and sensitivity to environmental signals. However these studies were restricted to a few genes, and the genome-wide picture remains unknown (Frei and Khammash, 2021; Weldemichael et al ., 2022). Overall, there is no clear evidence that specific network structures are involved in the regulation of plastic genes.…”