Dynamic Multiplexed Control and Modeling of Optogenetic Systems Using the High-Throughput Optogenetic Platform, Lustro

The ability to control cellular processes using optogenetics is inducer-limited, with most optogenetic systems responding to blue light. To address this limitation, we leverage an integrated framework combining Lustro, a powerful high-throughput optogenetics platform, and machine learning tools to enable multiplexed control over blue light-sensitive optogenetic systems. Specifically, we identify light induction conditions for sequential activation as well as preferential activation and switching between pairs of light-sensitive split transcription factors in the budding yeast, Saccharomyces cerevisiae. We use the high-throughput data generated from Lustro to build a Bayesian optimization framework that incorporates data-driven learning, uncertainty quantification, and experimental design to enable the prediction of system behavior and the identification of optimal conditions for multiplexed control. This work lays the foundation for designing more advanced synthetic biological circuits incorporating optogenetics, where multiple circuit components can be controlled using designer light induction programs, with broad implications for biotechnology and bioengineering.

Lustro: High-Throughput Optogenetic Experiments Enabled by Automation and a Yeast Optogenetic Toolkit

Optogenetic systems use genetically encoded light-sensitive proteins to control cellular processes. This provides the potential to orthogonally control cells with light; however, these systems require many design-build-test cycles to achieve a functional design and multiple illumination variables need to be laboriously tuned for optimal stimulation. We combine laboratory automation and a modular cloning scheme to enable high-throughput construction and characterization of optogenetic split transcription factors in Saccharomyces cerevisiae. We expand the yeast optogenetic toolkit to include variants of the cryptochromes and enhanced Magnets, incorporate these light-sensitive dimerizers into split transcription factors, and automate illumination and measurement of cultures in a 96-well microplate format for high-throughput characterization. We use this approach to rationally design and test an optimized enhanced Magnet transcription factor with improved light-sensitive gene expression. This approach is generalizable to the high-throughput characterization of optogenetic systems across a range of biological systems and applications.

Performance Prediction of Fundamental Transcriptional Programs

Transcriptional programming leverages systems of engineered transcription factors to impart decision-making (e.g., Boolean logic) in chassis cells. The number of components used to construct said decision-making systems is rapidly increasing, making an exhaustive experimental evaluation of iterations of biological circuits impractical. Accordingly, we posited that a predictive tool is needed to guide and accelerate the design of transcriptional programs. The work described here involves the development and experimental characterization of a large collection of network-capable single-INPUT logical operations─i.e., engineered BUFFER (repressor) and engineered NOT (antirepressor) logical operations. Using this single-INPUT data and developed metrology, we were able to model and predict the performances of all fundamental two-INPUT compressed logical operations (i.e., compressed AND gates and compressed NOR gates). In addition, we were able to model and predict the performance of compressed mixed phenotype logical operations (A NIMPLY B gates and complementary B NIMPLY A gates). These results demonstrate that single-INPUT data is sufficient to accurately predict both the qualitative and quantitative performance of a complex circuit. Accordingly, this work has set the stage for the predictive design of transcriptional programs of greater complexity.

RNA Viral Vectors for Accelerating Plant Synthetic Biology

The tools of synthetic biology have enormous potential to help us uncover the fundamental mechanisms controlling development and metabolism in plants. However, their effective utilization typically requires transgenesis, which is plagued by long timescales and high costs. In this review we explore how transgenesis can be minimized by delivering foreign genetic material to plants with systemically mobile and persistent vectors based on RNA viruses. We examine the progress that has been made thus far and highlight the hurdles that need to be overcome and some potential strategies to do so. We conclude with a discussion of biocontainment mechanisms to ensure these vectors can be used safely as well as how these vectors might expand the accessibility of plant synthetic biology techniques. RNA vectors stand poised to revolutionize plant synthetic biology by making genetic manipulation of plants cheaper and easier to deploy, as well as by accelerating experimental timescales from years to weeks.

Cell-free gene-regulatory network engineering with synthetic transcription factors

Gene-regulatory networks are ubiquitous in nature and critical for bottom-up engineering of synthetic networks. Transcriptional repression is a fundamental function that can be tuned at the level of DNA, protein, and cooperative protein-protein interactions, necessitating high-throughput experimental approaches for in-depth characterization. Here, we used a cell-free system in combination with a high-throughput microfluidic device to comprehensively study the different tuning mechanisms of a synthetic zinc-finger repressor library, whose affinity and cooperativity can be rationally engineered. The device is integrated into a comprehensive workflow that includes determination of transcription-factor binding-energy landscapes and mechanistic modeling, enabling us to generate a library of well-characterized synthetic transcription factors and corresponding promoters, which we then used to build gene-regulatory networks de novo. The well-characterized synthetic parts and insights gained should be useful for rationally engineering gene-regulatory networks and for studying the biophysics of transcriptional regulation.

Directed Evolution of Reprogramming Factors by Cell Selection and Sequencing

Directed biomolecular evolution is widely used to tailor and enhance enzymes, fluorescent proteins, and antibodies but has hitherto not been applied in the reprogramming of mammalian cells. Here, we describe a method termed directed evolution of reprogramming factors by cell selection and sequencing (DERBY-seq) to identify artificially enhanced and evolved reprogramming transcription factors. DERBY-seq entails pooled screens with libraries of positionally randomised genes, cell selection based on phenotypic readouts, and genotyping by amplicon sequencing for candidate identification. We benchmark this approach using pluripotency reprogramming with libraries based on the reprogramming factor SOX2 and the reprogramming incompetent endodermal factor SOX17. We identified several SOX2 variants outperforming the wild-type protein in three- and four-factor cocktails. The most effective variants were discovered from the SOX17 library, demonstrating that this factor can be converted into a highly potent inducer of pluripotency with a range of diverse modifications. We propose DERBY-seq as a broad-based approach to discover reprogramming factors for any donor/target cell combination applicable to direct lineage reprogramming in vitro and in vivo.

Randomized CRISPR-Cas Transcriptional Perturbation Screening Reveals Protective Genes against Alpha-Synuclein Toxicity

The genome-wide perturbation of transcriptional networks with CRISPR-Cas technology has primarily involved systematic and targeted gene modulation. Here, we developed PRISM (Perturbing Regulatory Interactions by Synthetic Modulators), a screening platform that uses randomized CRISPR-Cas transcription factors (crisprTFs) to globally perturb transcriptional networks. By applying PRISM to a yeast model of Parkinson's disease (PD), we identified guide RNAs (gRNAs) that modulate transcriptional networks and protect cells from alpha-synuclein (αSyn) toxicity. One gRNA identified in this screen outperformed the most protective suppressors of αSyn toxicity reported previously, highlighting PRISM's ability to identify modulators of important phenotypes. Gene expression profiling revealed genes differentially modulated by this strong protective gRNA that rescued yeast from αSyn toxicity when overexpressed. Human homologs of top-ranked hits protected against αSyn-induced cell death in a human neuronal PD model. Thus, high-throughput and unbiased perturbation of transcriptional networks via randomized crisprTFs can reveal complex biological phenotypes and effective disease modulators.

Engineering Synthetic Gene Circuits in Living Cells with CRISPR Technology

One of the goals of synthetic biology is to build regulatory circuits that control cell behavior, for both basic research purposes and biomedical applications. The ability to build transcriptional regulatory devices depends on the availability of programmable, sequence-specific, and effective synthetic transcription factors (TFs). The prokaryotic clustered regularly interspaced short palindromic repeat (CRISPR) system, recently harnessed for transcriptional regulation in various heterologous host cells, offers unprecedented ease in designing synthetic TFs. We review how CRISPR can be used to build synthetic gene circuits and discuss recent advances in CRISPR-mediated gene regulation that offer the potential to build increasingly complex, programmable, and efficient gene circuits in the future.

Specific induction of endogenous viral restriction factors using CRISPR/Cas-derived transcriptional activators

Whereas several mammalian proteins can restrict the replication of HIV-1 and other viruses, these are often not expressed in relevant target cells. A potential method to inhibit viral replication might therefore be to use synthetic transcription factors to induce restriction factor expression. In particular, mutants of the RNA-guided DNA binding protein Cas9 that have lost their DNA cleavage activity could be used to recruit transcription activation domains to specific promoters. However, initial experiments revealed only weak activation unless multiple promoter-specific single guide RNAs (sgRNAs) were used. Recently, the recruitment of multiple transcription activation domains by a single sgRNA, modified to contain MS2-derived stem loops that recruit fusion proteins consisting of the MS2 coat protein linked to transcription activation domains, was reported to induce otherwise silent cellular genes. Here, we demonstrate that such "synergistic activation mediators" can induce the expression of two restriction factors, APOBEC3G (A3G) and APOBEC3B (A3B), in human cells that normally lack these proteins. We observed modest activation of endogenous A3G or A3B expression using single sgRNAs but high expression when two sgRNAs were used. Whereas the induced A3G and A3B proteins both blocked infection by an HIV-1 variant lacking a functional vif gene by inducing extensive dC-to-dU editing, only the induced A3B protein inhibited wild-type HIV-1. These data demonstrate that Cas9-derived transcriptional activators have the potential to be used for screens for endogenous genes that affect virus replication and raise the possibility that synthetic transcription factors might prove clinically useful if efficient delivery mechanisms could be developed.

NanoScript: a nanoparticle-based artificial transcription factor for effective gene regulation

Transcription factor (TF) proteins are master regulators of transcriptional activity and gene expression. TF-based gene regulation is a promising approach for many biological applications; however, several limitations hinder the full potential of TFs. Herein, we developed an artificial, nanoparticle-based transcription factor, termed NanoScript, which is designed to mimic the structure and function of TFs. NanoScript was constructed by tethering functional peptides and small molecules called synthetic transcription factors, which mimic the individual TF domains, onto gold nanoparticles. We demonstrate that NanoScript localizes within the nucleus and initiates transcription of a reporter plasmid by over 15-fold. Moreover, NanoScript can effectively transcribe targeted genes on endogenous DNA in a nonviral manner. Because NanoScript is a functional replica of TF proteins and a tunable gene-regulating platform, it has great potential for various stem cell applications.