Farren J. Isaacs

Programming cells by multiplex genome engineering and accelerated evolution

The breadth of genomic diversity found among organisms in nature allows populations to adapt to diverse environments. However, genomic diversity is difficult to generate in the laboratory and new phenotypes do not easily arise on practical timescales. Although in vitro and directed evolution methods have created genetic variants with usefully altered phenotypes, these methods are limited to laborious and serial manipulation of single genes and are not used for parallel and continuous directed evolution of gene networks or genomes. Here, we describe multiplex automated genome engineering (MAGE) for large-scale programming and evolution of cells. MAGE simultaneously targets many locations on the chromosome for modification in a single cell or across a population of cells, thus producing combinatorial genomic diversity. Because the process is cyclical and scalable, we constructed prototype devices that automate the MAGE technology to facilitate rapid and continuous generation of a diverse set of genetic changes (mismatches, insertions, deletions). We applied MAGE to optimize the 1-deoxy-d-xylulose-5-phosphate (DXP) biosynthesis pathway in Escherichia coli to overproduce the industrially important isoprenoid lycopene. Twenty-four genetic components in the DXP pathway were modified simultaneously using a complex pool of synthetic DNA, creating over 4.3 billion combinatorial genomic variants per day. We isolated variants with more than fivefold increase in lycopene production within 3 days, a significant improvement over existing metabolic engineering techniques. Our multiplex approach embraces engineering in the context of evolution by expediting the design and evolution of organisms with new and improved properties.

COMPUTATIONAL STUDIES OF GENE REGULATORY NETWORKS: IN NUMERO MOLECULAR BIOLOGY

Remarkable progress in genomic research is leading to a complete map of the building blocks of biology. Knowledge of this map is, in turn, setting the stage for a fundamental description of cellular function at the DNA level. Such a description will entail an understanding of gene regulation, in which proteins often regulate their own production or that of other proteins in a complex web of interactions. The implications of the underlying logic of genetic networks are difficult to deduce through experimental techniques alone, and successful approaches will probably involve the union of new experiments and computational modelling techniques.

Engineered riboregulators enable post-transcriptional control of gene expression

Recent studies have demonstrated the important enzymatic, structural and regulatory roles of RNA in the cell. Here we present a post-transcriptional regulation system in Escherichia coli that uses RNA to both silence and activate gene expression. We inserted a complementary cis sequence directly upstream of the ribosome binding site in a target gene. Upon transcription, this cis-repressive sequence causes a stem-loop structure to form at the 5′–untranslated region of the mRNA. The stem-loop structure interferes with ribosome binding, silencing gene expression. A small noncoding RNA that is expressed in trans targets the cis-repressed RNA with high specificity, causing an alteration in the stem-loop structure that activates expression. Such engineered riboregulators may lend insight into mechanistic actions of endogenous RNA-based processes and could serve as scalable components of biological networks, able to function with any promoter or gene to directly control gene expression.

Prediction and measurement of an autoregulatory genetic module

The deduction of phenotypic cellular responses from the structure and behavior of complex gene regulatory networks is one of the defining challenges of systems biology. This goal will require a quantitative understanding of the modular components that constitute such networks. We pursued an integrated approach, combining theory and experiment, to analyze and describe the dynamics of an isolated genetic module, an in vivo autoregulatory gene network. As predicted by the model, temperature-induced protein destabilization led to the existence of two expression states, thus elucidating the trademark bistability of the positive feedback-network architecture. After sweeping the temperature, observed population distributions and coefficients of variation were in quantitative agreement with those predicted by a stochastic version of the model. Because model fluctuations originated from small molecule-number effects, the experimental validation underscores the importance of internal noise in gene expression. This work demonstrates that isolated gene networks, coupled with proper quantitative descriptions, can elucidate key properties of functional genetic modules. Such an approach could lead to the modular dissection of naturally occurring gene regulatory networks, the deduction of cellular processes such as differentiation, and the development of engineered cellular control.

Precise Manipulation of Chromosomes in Vivo Enables Genome-Wide Codon Replacement

Template-mediated, genome construction and assembly created a strain with 80 precise codon changes. We present genome engineering technologies that are capable of fundamentally reengineering genomes from the nucleotide to the megabase scale. We used multiplex automated genome engineering (MAGE) to site-specifically replace all 314 TAG stop codons with synonymous TAA codons in parallel across 32 Escherichia coli strains. This approach allowed us to measure individual recombination frequencies, confirm viability for each modification, and identify associated phenotypes. We developed hierarchical conjugative assembly genome engineering (CAGE) to merge these sets of codon modifications into genomes with 80 precise changes, which demonstrate that these synonymous codon substitutions can be combined into higher-order strains without synthetic lethal effects. Our methods treat the chromosome as both an editable and an evolvable template, permitting the exploration of vast genetic landscapes.

Genomically recoded organisms expand biological functions.

Changing the Code Easily and efficiently expanding the genetic code could provide tools to genome engineers with broad applications in medicine, energy, agriculture, and environmental safety. Lajoie et al. (p. 357) replaced all known UAG stop codons with synonymous UAA stop codons in Escherichia coli MG1655, as well as release factor 1 (RF1; terminates translation at UAG), thereby eliminating natural UAG translation function without impairing fitness. This made it possible to reassign UAG as a dedicated codon to genetically encode nonstandard amino acids while avoiding deleterious incorporation at native UAG positions. The engineered E. coli incorporated nonstandard amino acids into its proteins and showed enhanced resistance to bacteriophage T7. In a second paper, Lajoie et al. (p. 361) demonstrated the recoding of 13 codons in 42 highly expressed essential genes in E. coli. Codon usage was malleable, but synonymous codons occasionally were nonequivalent in unpredictable ways. Bacteria engineered to use nonstandard amino acids show increased resistance to bacteriophage attack. We describe the construction and characterization of a genomically recoded organism (GRO). We replaced all known UAG stop codons in Escherichia coli MG1655 with synonymous UAA codons, which permitted the deletion of release factor 1 and reassignment of UAG translation function. This GRO exhibited improved properties for incorporation of nonstandard amino acids that expand the chemical diversity of proteins in vivo. The GRO also exhibited increased resistance to T7 bacteriophage, demonstrating that new genetic codes could enable increased viral resistance.

RNA synthetic biology

RNA molecules play important and diverse regulatory roles in the cell by virtue of their interaction with other nucleic acids, proteins and small molecules. Inspired by this natural versatility, researchers have engineered RNA molecules with new biological functions. In the last two years efforts in synthetic biology have produced novel, synthetic RNA components capable of regulating gene expression in vivo largely in bacteria and yeast, setting the stage for scalable and programmable cellular behavior. Immediate challenges for this emerging field include determining how computational and directed-evolution techniques can be implemented to increase the complexity of engineered RNA systems, as well as determining how such systems can be broadly extended to mammalian systems. Further challenges include designing RNA molecules to be sensors of intracellular and environmental stimuli, probes to explore the behavior of biological networks and components of engineered cellular control systems.

Designer gene networks: Towards fundamental cellular control

The engineered control of cellular function through the design of synthetic genetic networks is becoming plausible. Here we show how a naturally occurring network can be used as a parts list for artificial network design, and how model formulation leads to computational and analytical approaches relevant to nonlinear dynamics and statistical physics. We first review the relevant work on synthetic gene networks, highlighting the important experimental findings with regard to genetic switches and oscillators. We then present the derivation of a deterministic model describing the temporal evolution of the concentration of protein in a single-gene network. Bistability in the steady-state protein concentration arises naturally as a consequence of autoregulatory feedback, and we focus on the hysteretic properties of the protein concentration as a function of the degradation rate. We then formulate the effect of an external noise source which interacts with the protein degradation rate. We demonstrate the utility of such a formulation by constructing a protein switch, whereby external noise pulses are used to switch the protein concentration between two values. Following the lead of earlier work, we show how the addition of a second network component can be used to construct a relaxation oscillator, whereby the system is driven around the hysteresis loop. We highlight the frequency dependence on the tunable parameter values, and discuss design plausibility. We emphasize how the model equations can be used to develop design criteria for robust oscillations, and illustrate this point with parameter plots illuminating the oscillatory regions for given parameter values. We then turn to the utilization of an intrinsic cellular process as a means of controlling the oscillations. We consider a network design which exhibits self-sustained oscillations, and discuss the driving of the oscillator in the context of synchronization. Then, as a second design, we consider a synthetic network with parameter values near, but outside, the oscillatory boundary. In this case, we show how resonance can lead to the induction of oscillations and amplification of a cellular signal. Finally, we construct a toggle switch from positive regulatory elements, and compare the switching properties for this network with those of a network constructed using negative regulation. Our results demonstrate the utility of model analysis in the construction of synthetic gene regulatory networks. (c) 2001 American Institute of Physics.

A-to-I RNA editing occurs at over a hundred million genomic sites, located in a majority of human genes

RNA molecules transmit the information encoded in the genome and generally reflect its content. Adenosine-to-inosine (A-to-I) RNA editing by ADAR proteins converts a genomically encoded adenosine into inosine. It is known that most RNA editing in human takes place in the primate-specific Alu sequences, but the extent of this phenomenon and its effect on transcriptome diversity are not yet clear. Here, we analyzed large-scale RNA-seq data and detected ∼1.6 million editing sites. As detection sensitivity increases with sequencing coverage, we performed ultradeep sequencing of selected Alu sequences and showed that the scope of editing is much larger than anticipated. We found that virtually all adenosines within Alu repeats that form double-stranded RNA undergo A-to-I editing, although most sites exhibit editing at only low levels (<1%). Moreover, using high coverage sequencing, we observed editing of transcripts resulting from residual antisense expression, doubling the number of edited sites in the human genome. Based on bioinformatic analyses and deep targeted sequencing, we estimate that there are over 100 million human Alu RNA editing sites, located in the majority of human genes. These findings set the stage for exploring how this primate-specific massive diversification of the transcriptome is utilized.

Tracking, tuning, and terminating microbial physiology using synthetic riboregulators

The development of biomolecular devices that interface with biological systems to reveal new insights and produce novel functions is one of the defining goals of synthetic biology. Our lab previously described a synthetic, riboregulator system that affords for modular, tunable, and tight control of gene expression in vivo. Here we highlight several experimental advantages unique to this RNA-based system, including physiologically relevant protein production, component modularity, leakage minimization, rapid response time, tunable gene expression, and independent regulation of multiple genes. We demonstrate this utility in four sets of in vivo experiments with various microbial systems. Specifically, we show that the synthetic riboregulator is well suited for GFP fusion protein tracking in wild-type cells, tight regulation of toxic protein expression, and sensitive perturbation of stress response networks. We also show that the system can be used for logic-based computing of multiple, orthogonal inputs, resulting in the development of a programmable kill switch for bacteria. This work establishes a broad, easy-to-use synthetic biology platform for microbiology experiments and biotechnology applications.