Transcriptional regulation is central to the complex behavior of natural biological systems and synthetic gene circuits. Platforms for the scalable, tunable, and simple modulation of transcription would enable new abilities to study natural systems and implement artificial capabilities in living cells. Previous approaches to synthetic transcriptional regulation have relied on engineering DNA-binding proteins, which necessitate multistep processes for construction and optimization of function. Here, we show that the CRISPR/Cas system of Streptococcus pyogenes can be programmed to direct both activation and repression to natural and artificial eukaryotic promoters through the simple engineering of guide RNAs with base-pairing complementarity to target DNA sites. We demonstrate that the activity of CRISPR-based transcription factors (crisprTFs) can be tuned by directing multiple crisprTFs to different positions in natural promoters and by arraying multiple crisprTF-binding sites in the context of synthetic promoters in yeast and human cells. Furthermore, externally controllable regulatory modules can be engineered by layering gRNAs with small molecule-responsive proteins. Additionally, single nucleotide substitutions within promoters are sufficient to render them orthogonal with respect to the same gRNA-guided crisprTF. We envision that CRISPR-based eukaryotic gene regulation will enable the facile construction of scalable synthetic gene circuits and open up new approaches for mapping natural gene networks and their effects on complex cellular phenotypes.

Cellular memory is crucial to many natural biological processes and for sophisticated synthetic-biology applications. Existing cellular memories rely on epigenetic switches or recombinases, which are limited in scalability and recording capacity. Here, we use the DNA of living cell populations as genomic ‘tape recorders’ for the analog and distributed recording of long-term event histories. We describe a platform for generating single-stranded DNA (ssDNA) in vivo in response to arbitrary transcriptional signals. When co-expressed with a recombinase, these intracellularly expressed ssDNAs target specific genomic DNA addresses, resulting in precise mutations that accumulate in cell populations as a function of the magnitude and duration of the inputs. This platform could enable long-term cellular recorders for environmental and biomedical applications, biological state machines, and enhanced genome engineering strategies.

Natural life is encoded by evolvable, DNA-based memory. Recent advances in dynamic genome-engineering technologies, which we collectively refer to as in vivo DNA writing, have opened new avenues for investigating and engineering biology. This Review surveys these technological advances, outlines their prospects and emerging applications, and discusses the features and current limitations of these technologies for building various genetic circuits for processing and recording information in living cells.

to encode a wide range of order-independent, sequential, and temporal logic and memory 26 operations. Furthermore, we show that these operators can be used to perform both digital and 27 analog computation, and record signaling dynamics and cellular states in a long-term, autonomous, 28 and minimally disruptive fashion. Finally, we show that the platform can be functionalized with The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/263657 doi: bioRxiv preprint first posted online Feb. 15, 2018; 3 Main Text: 40 Robust and scalable molecular recording and computation platforms in living cells are key to 41 enabling a broad range of bioengineering and biomedical applications. Unlike their silicon-based 42 counterparts that have access to large capacities of addressable memory registers, synthetic genetic 43 circuits currently have very limited information storage capacities and existing methods for 44 encoding information into cellular memory, as well as strategies for integrating such memory with 45 logic operations, are challenging to scale. 46 Genomic DNA is an ideal medium for biological memory since it is ubiquitously present, 47 naturally replicated at high fidelity within cells, and compatible with natural biological operations. 48 In recent years, several strategies for encoding biological information into DNA and integrating 49 these memories with cellular computers have been described (Farzadfard and Lu, 2014; Kalhor et 50 al., 2017; McKenna et al., 2016; Perli et al., 2016; Roquet et al., 2016; Siuti et al., 2013). However, 51 these methods remain limited in their encoding capacity and scalability. For example, site-specific 52 recombinases that flip or excise targeted DNA segments have been used to create digital memory, 53 sequential logic, and biological state machines in living cells (Roquet et al., 2016; Siuti et al., 54 2013). However, a different recombinase is required for every unique event that one wishes to 55 record, thus limiting the number of potential states that can be encoded into DNA memory. 56 Furthermore, distances between recombinase-recognition sites usually need to be several hundred 57 base pairs to achieve efficient recombination, thus increasing circuit size (Coppoolse et al., 2005; 58 Stark, 2017). Furthermore, recombinase sites must be pre-engineered into desired target sites, 59 which is time-and labor-intensive, especially if they are to be used in the genomic context. 60 To address these limitations, we previously developed the SCRIBE DNA writing and 61 molecular recording system, which uses in vivo single-stranded DNA expression to generate 62 precise mutations that accumulate into target genomic loci as a function of the magnitude and 63 duration of exposure to an input (Farzadfard and Lu, 2014). However, this approach has been 64 limited to bacteria thus far due to the requirement for specific recombination mechanisms. 65Alternative molecular recording strategies based on Cas9 ...