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Del Vecchio, D.

Publications and source records attributed to Del Vecchio, D..

6 recordsLinked to original sources

A quasi-integral controller for adaptation of genetic modules to variable ribosome demand

The behavior of genetic circuits is often poorly predictable. A genes expression level is not only determined by the intended regulators, but also largely dictated by changes in ribosome availability imparted by activation or repression of other genes. To address this problem, we design a quasi-integral biomolecular feedback controller that enables the expression level of any gene of interest (GOI) to adapt to changes in available ribosomes. The feedback is implemented through a synthetic small RNA (sRNA) that silences the GOIs mRNA, and uses orthogonal extracytoplasmic function (ECF) sigma factor to sense the GOIs translation and to actuate sRNA transcription. Without the controller, the expression level of the GOI is reduced by 50% when a resource competitor is activated. With the controller, by contrast, gene expression level is practically unaffected by the competitor. This feedback controller allows adaptation of genetic modules to variable ribosome demand and thus aids modular construction of complicated circuits.

synthetic biology

A Model for Resource Competition in CRISPR-Mediated Gene Repression

CRISPR-mediated gene regulation is known for its ability to control multiple targets simultaneously due to its modular nature: the same dCas9 effector can target different genes simply by changing the associated gRNA. However, multiplexing requires the sharing of limited amounts of dCas9 proteins among multiple gRNAs, leading to resource competition. In turn, competition between gRNAs for the same resource may hamper network function. In this work, we develop a general model that takes into account the sharing of a limited amount of dCas9 protein for arbitrary CRISPR-mediated gene repression networks. We demonstrate that, as a result of resource competition, hidden interactions appear, that modify the intended network regulations. As a case study, we analyze the effects of these hidden interactions in repression cascades. In particular, we illustrate that perfect adaptation to resource fluctuations can be achieved in cascades with an even number of repressors. In contrast, cascades with an odd number of repressors are substantially impacted by resource competition.

synthetic biology

Realizing "Integral Control" In Living Cells: How To Overcome Leaky Integration Due To Dilution?

A major problem in the design of synthetic genetic circuits is robustness to perturbations and uncertainty. Because of this, there have been significant efforts in recent years in finding approaches to implement integral control in genetic circuits. Integral controllers have the unique ability to make the output of a process adapt perfectly to disturbances. However, implementing an integral controller is challenging in living cells. This is because a key aspect of any integral controller is a \"memory\" element that stores the accumulation (integral) of the error between the output and its desired set-point. The ability to realize such a memory element in living cells is fundamentally challenged by the fact that all biomolecules dilute as cells grow, resulting in a \"leaky\" memory that gradually fades away. As a consequence, the adaptation property is lost. Here, we propose a general principle for designing integral controllers such that the performance is practically unaffected by dilution. In particular, we mathematically prove that if the reactions implementing the integral controller are all much faster than dilution, then the adaptation error due to integration leakiness becomes negligible. We exemplify this design principle with two synthetic genetic circuits aimed at reaching adaptation of gene expression to fluctuations in cellular resources. Our results provide concrete guidance on the biomolecular processes that are most appropriate for implementing integral controllers in living cells.

synthetic biology

Signaling architectures that transmit unidirectional information despite retroactivity

A signaling pathway transmits information from an upstream system to downstream systems, ideally in a unidirectional fashion. A key obstacle to unidirectional transmission is retroactivity, the additional reaction flux that affects a system once its species interact with those of downstream systems. This raises the fundamental question of whether signaling pathways have developed specialized architectures that overcome retroactivity and transmit unidirectional signals. Here, we propose a general procedure based on mathematical analysis that provides an answer to this question. Using this procedure, we analyze the ability of a variety of signaling architectures to transmit one-way (from upstream to downstream) signals, as key biological parameters are tuned. We find that single stage phosphorylation and phosphotransfer systems that transmit signals from a kinase show a stringent design trade-off that hampers their ability to overcome retroactivity. Interestingly, cascades of these architectures, which are highly represented in nature, can overcome this trade-off and thus enable unidirectional transmission. By contrast, phosphotransfer systems, and single and double phosphorylation cycles that transmit signals from a substrate are unable to mitigate retroactivity effects, even when cascaded, and hence are not well suited for unidirectional information transmission. Our results identify signaling architectures that, allowing unidirectional transmission of signals, embody modular processes that conserve their input/output behavior across multiple contexts. These findings can be used to decompose natural signal transduction networks into modules, and, at the same time, they establish a library of devices that can be used in synthetic biology to facilitate modular circuit design.

biophysics

Resource Competition Shapes the Response of Genetic Circuits

A common approach to design genetic circuits is to compose gene expression cassettes together. While appealing, this modular approach is challenged by the fact that expression of each gene depends on the availability of transcriptional/translational resources, which is in turn determined by the presence of other genes in the circuit. This raises the question of how competition for resources by different genes affects a circuits behavior. Here, we create a library of genetic activation cascades in bacteria E. coli, where we explicitly tune the resource demand by each gene. We develop a general Hill-function-based model that incorporates resource competition effects through resource demand coefficients. These coefficients lead to non-regulatory interactions among genes that reshape circuits behavior. For the activation cascade, such interactions result in surprising biphasic or monotonically decreasing responses. Finally, we use resource demand coefficients to guide the choice of ribosome binding site (RBS) and DNA copy number to restore the cascades intended monotonically increasing response. Our results demonstrate how unintended circuits behavior arises from resource competition and provide a model-guided methodology to minimize the resulting effects.\n\nO_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

synthetic biology

The Effect of Compositional Context on Synthetic Gene Net-works

It is well known that synthetic gene expression is highly sensitive to how comprising genetic elements (promoter structure, spacing regions between promoter and coding sequences, ribosome binding sites, etc.) are spatially configured. An important topic that has received far less attention is how the physical layout of entire genes within a synthetic gene network affects their individual expression levels. In this paper we show, both quantitatively and qualitatively, that compositional context can significantly alter expression levels in synthetic gene networks. We also show that these compositional context effects are pervasive both at the transcriptional and translational level. Further, we demonstrate that key characteristics of gene induction, such as ultra-sensitivity and dynamic range, are heavily dependent on compositional context. We postulate that supercoiling can be used to explain these interference effects and validate this hypothesis through modeling and a series of in vitro supercoiling relaxation experiments. On the whole, these results suggest that compositional context introduces feedback in synthetic gene networks. As an illustrative example, we show that a design strategy incorporating compositional context effects can improve threshold detection and memory properties of the toggle switch.

synthetic biology