Alfonso Jaramillo

Dynamic signal processing by ribozyme-mediated RNA circuits to control gene expression

Organisms have different circuitries that allow converting signal molecule levels to changes in gene expression. An important challenge in synthetic biology involves the de novo design of RNA modules enabling dynamic signal processing in live cells. This requires a scalable methodology for sensing, transmission, and actuation, which could be assembled into larger signaling networks. Here, we present a biochemical strategy to design RNA-mediated signal transduction cascades able to sense small molecules and small RNAs. We design switchable functional RNA domains by using strand-displacement techniques. We experimentally characterize the molecular mechanism underlying our synthetic RNA signaling cascades, show the ability to regulate gene expression with transduced RNA signals, and describe the signal processing response of our systems to periodic forcing in single live cells. The engineered systems integrate RNA–RNA interaction with available ribozyme and aptamer elements, providing new ways to engineer arbitrary complex gene circuits.

RiboMaker: computational design of conformation-based riboregulation

MOTIVATIONnThe ability to engineer control systems of gene expression is instrumental for synthetic biology. Thus, bioinformatic methods that assist such engineering are appealing because they can guide the sequence design and prevent costly experimental screening. In particular, RNA is an ideal substrate to de novo design regulators of protein expression by following sequence-to-function models.nnnRESULTSnWe have implemented a novel algorithm, RiboMaker, aimed at the computational, automated design of bacterial riboregulation. RiboMaker reads the sequence and structure specifications, which codify for a gene regulatory behaviour, and optimizes the sequences of a small regulatory RNA and a 5-untranslated region for an efficient intermolecular interaction. To this end, it implements an evolutionary design strategy, where random mutations are selected according to a physicochemical model based on free energies. The resulting sequences can then be tested experimentally, providing a new tool for synthetic biology, and also for investigating the riboregulation principles in natural systems.nnnAVAILABILITY AND IMPLEMENTATIONnWeb server is available at http://ribomaker.jaramillolab.org/. Source code, instructions and examples are freely available for download at http://sourceforge.net/projects/ribomaker/.

Using promoter libraries to reduce metabolic burden due to plasmid-encoded proteins in recombinant Escherichia coli

The over-expression of proteins in recombinant host cells often requires a significant amount of resources causing an increase in the metabolic load for the host. This results in a variety of physiological responses leading to altered growth parameters, including growth inhibition or activation of secondary metabolism pathways. Moreover, the expression of other plasmid-encoded genes such as antibiotic resistance genes or repressor proteins may also alter growth kinetics. In this work, we have developed a second-generation system suitable for Escherichia coli expression with an antibiotic-free plasmid maintenance mechanism based on a glycine auxotrophic marker (glyA). Metabolic burden related to plasmid maintenance and heterologous protein expression was minimized by tuning the expression levels of the repressor protein (LacI) and glyA using a library of promoters and applying synthetic biology tools that allow the rapid construction of vectors. The engineered antibiotic-free expression system was applied to the L-fuculose phosphate aldolase (FucA) over-production, showing an increase in production up to 3.8-fold in terms of FucA yield (mg g(-1)DCW) and 4.5-fold in terms of FucA activity (AU g(-1)DCW) compared to previous expression. Moreover, acetic acid production was reduced to 50%, expressed as gAc gDCW(-1). Our results showed that the aforementioned approaches are of paramount importance in order to increment the protein production in terms of mass and activity.

Bacterial computing with engineered populations

We describe strategies for the construction of bacterial computing platforms by describing a number of results from the recently completed bacterial computing with engineered populations project. In general, the implementation of such systems requires a framework containing various components such as intracellular circuits, single cell input/output and cell–cell interfacing, as well as extensive analysis. In this overview paper, we describe our approach to each of these, and suggest possible areas for future research.

Functionalization of an Antisense Small RNA.

In order to explore the possibility of adding new functions to preexisting genes, we considered a framework of riboregulation. We created a new riboregulator consisting of the reverse complement of a known riboregulator. Using computational design, we engineered a cis-repressing 5 untranslated region that can be activated by this new riboregulator. As a result, both RNAs can orthogonally trans-activate translation of their cognate, independent targets. The two riboregulators can also repress each other by antisense interaction, although not symmetrically. Our work highlights that antisense small RNAs can work as regulatory agents beyond the antisense paradigm and that, hence, they could be interfaced with other circuits used in synthetic biology.

Exploring the dynamics and mutational landscape of riboregulation with a minimal synthetic circuit in living cells

The regulation of gene expression, triggered by conformational changes in RNA molecules, is widely observed in cellular systems. Here, we examine this mode of control by means of a model-based design and construction of a fully synthetic riboregulatory device. We present a theoretical framework that rests on a simple energy model to predict the dynamic response of such a system. Following an equilibrium description, our framework integrates thermodynamic properties—anticipated with an RNA physicochemical model—with a detailed description of the intermolecular interaction. The theoretical calculations are confirmed with an experimental characterization of the action of the riboregulatory device within living cells. This illustrates, more broadly, the predictability of genetic robustness on synthetic systems, and the faculty to engineer gene expression programs from a minimal set of first principles.

Model-based design of RNA hybridization networks implemented in living cells.

Abstract Synthetic gene circuits allow the behavior of living cells to be reprogrammed, and non-coding small RNAs (sRNAs) are increasingly being used as programmable regulators of gene expression. However, sRNAs (natural or synthetic) are generally used to regulate single target genes, while complex dynamic behaviors would require networks of sRNAs regulating each other. Here, we report a strategy for implementing such networks that exploits hybridization reactions carried out exclusively by multifaceted sRNAs that are both targets of and triggers for other sRNAs. These networks are ultimately coupled to the control of gene expression. We relied on a thermodynamic model of the different stable conformational states underlying this system at the nucleotide level. To test our model, we designed five different RNA hybridization networks with a linear architecture, and we implemented them in Escherichia coli. We validated the network architecture at the molecular level by native polyacrylamide gel electrophoresis, as well as the network function at the bacterial population and single-cell levels with a fluorescent reporter. Our results suggest that it is possible to engineer complex cellular programs based on RNA from first principles. Because these networks are mainly based on physical interactions, our designs could be expanded to other organisms as portable regulatory resources or to implement biological computations.

Regulatory RNA Design Through Evolutionary Computation and Strand Displacement

The discovery and study of a vast number of regulatory RNAs in all kingdoms of life over the past decades has allowed the design of new synthetic RNAs that can regulate gene expression in vivo. Riboregulators, in particular, have been used to activate or repress gene expression. However, to accelerate and scale up the design process, synthetic biologists require computer-assisted design tools, without which riboregulator engineering will remain a case-by-case design process requiring expert attention. Recently, the design of RNA circuits by evolutionary computation and adapting strand displacement techniques from nanotechnology has proven to be suited to the automated generation of DNA sequences implementing regulatory RNA systems in bacteria. Herein, we present our method to carry out such evolutionary design and how to use it to create various types of riboregulators, allowing the systematic de novo design of genetic control systems in synthetic biology.

Quantitative Characterization of Translational Riboregulators Using an in Vitro Transcription–Translation System

Riboregulators are short RNA sequences that, upon binding to a ligand, change their secondary structure and influence the expression rate of a downstream gene. They constitute an attractive alternative to transcription factors for building synthetic gene regulatory networks because they can be engineered de novo. However, riboregulators are generally designed in silico and tested in vivo, which provides little quantitative information about their performances, thus hindering the improvement of design algorithms. Here we show that a cell-free transcription-translation (TX-TL) system provides valuable information about the performances of in silico designed riboregulators. We first propose a simple model that provides a quantitative definition of the dynamic range of a riboregulator. We further characterize two types of translational riboregulators composed of a cis-repressed (cr) and a trans-activating (ta) strand. At the DNA level we demonstrate that high concentrations of taDNA poisoned the activator until total shut off, in agreement with our model, and that relative dynamic ranges of riboregulators determined in vitro are in agreement with published in vivo data. At the RNA level, we show that this approach provides a fast and simple way to measure dissociation constants of functional riboregulators, in contrast to standard mobility-shift assays. Our method opens the route for using cell-free TX-TL systems for the quantitative characterization of functional riboregulators in order to improve their design in silico.

Cooperative riboregulation in living cells through allosteric programming of toehold activation

Living cells rely on small non-coding RNAs (sRNAs) to regulate gene expression at the post-transcriptional level. Contrary to most protein-based activators of transcription, all known riboregulators do not exploit cooperative binding mechanisms to activate gene expression. We conceived a general strategy to design cooperative riboregulation by programming a hierarchical toehold activation cascade, which we implemented into a de novo sequence design algorithm. We engineered different riboregulatory systems relying on the conditional formation of a heterotrimeric species. We characterized the specificity of each RNA-RNA interaction in vitro and the cooperative activation of gene expression in Escherichia coli. As we only rely on a biochemical model to compute allosteric regulation, our strategy could be applied to reach more complex RNA-based nanostructures regulating gene expression for synthetic biology applications.