Design in E. Coli

The synthetic transcription factor: dCas9-w

We will use the DNA-binding activity of the catalytically 'dead' version of Cas9, dCas9, to regulate genes.

For activation to be possible, dCas9 needs to be fused to a RNA polymerase (RNAP) recruiting element

. We fused the

ω (omega) subunit of RNAP to dCas9 [1]. The ω subunit works as a RNAP recruiting element in E. coli when working in a strain in which RNAP lacks the ω subunit. We used JEN202, "an E. coli MG1655 mutant in which rpoZ, encoding for the ω subunit of RNAP, was replaced by a spectinomycin resistance gene" [1], for all fluorescence measurements.

We used single guide RNAs (sgRNA) to guide dCas9-w to targetted regions. An sgRNA "comprises a complementary domain that binds to the DNA followed by a “handle” that is bound by dCas9" [3]: in our case dCas9-w. dCas9-w and an sgRNA form a complex which will tightly bind a DNA sequence complementary to the 'complementary domain' of the sgRNA.

Find out how we regulate genes with dCas9-w below!

The bio-transistor

The bio-transistor for E. coli consists of a gene controlled by a synthetic promoter.

We synthesized promoters based on the constituve promoter J23117 [1]. This promoter consists of BBa_J233117, preceded by a protospacer-adjacent motif (PAM) [4] rich upstream regulating sequence (URS).

We tested our system for the promoter J23117 and J23117alt. The sequence for J23117alt was randomely generated, except for the -35 and -10 regions that we conserved. Some of our team members wrote a program in C++ and then in Python that generated a random sequence that conserved part of an original sequence. To observe the activity of a single bio-transistor, we used a gene encoding for green fluorescent protein (GFP) as a reporter gene.

If dCas9-w guided by an sgRNA binds on the promoter close to the transcription start site, the binding of RNAP to DNA is sterically inhibited, and transcription is repressed. We chose to use sgRNAs complementary to sequences 14 or 18 bp upstream from the transcription start site (TSS). If dCas9-w guided by an sgRNA binds at an optimal distance upstream from the promoter, the ω subunit recruits RNAP and transcription is activated. We chose to use sgRNAs complementary to the sequence 71 bp upstream from the TSS. [1]
If both the inhibiting and the activating sgRNA for the same promoter are present in the same cell, we foresaw 2 possible situations. We simulated both with our model: either dCas9-w can bind both the activating and the inhibiting sites, in this case the model predicts that the inhibitory will tend to be stronger, or dCas9-w cannot bind both sites due to sterical hindrance in which case the overal effect should tend to be activating. For more information on these situations, check out our Modeling page, or see how this turned out experimentally in our Results!

We constructed plasmid pdCas9-w, encoding for dCas9-w controlled by a Tetracylcine-inducible promoter, from pdCas9-bacteria [2] and pWJ66 [1]. We synthesized 'sgRNA expressing cassettes' (IDT) controlled by a constitutive promoter and inserted these into pdCas9-w. We inserted either one sgRNA (activating or inhibiting) or two sgRNA (1 activating and 1 inhibiting, or 2 inhibiting, affecting the same promoter). We used pWJ89, GFP controlled by the J23117 promoter, [1] as the first 'reporter-transistor'. We constructed pWJ89alt, GFP controlled by the J23117alt promoter, as our second 'reporter-transistor'.

We transformed JEN202 cells with one of the 'reporter-transistors' and pdCas9-w with sgRNAs complementary to the activating and/or inhibiting regions of the promoter of the transistor, and measured the fluorescence of these cells with a plate reader or by flow cytometry. See the results here.

References

[1] Bikard, D., Jiang, W., Samai, P., Hochschild, A., Zhang, F., & Marraffini, L. A. (2013). Programmable repression and activation of bacterial gene expression using an engineered CRISPR-Cas system. Nucleic acids research, 41(15), 7429-7437.
[2] Qi, L. S., Larson, M. H., Gilbert, L. A., Doudna, J. A., Weissman, J. S., Arkin, A. P., & Lim, W. A. (2013). Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression. Cell, 152(5), 1173-1183.
[3] Alec AK Nielsen & Christopher A Voigt (2014). Multi-input CRISPR/Cas circuits that interface host regulatory network. Molecular systems biology, 10(11), 763.
[4] Addgene about protospacer-adjacent motif (PAM)

Design in yeast

Elements of the transistor

Transistor

Logic gate

Background

Programmable cells - Promises and Limitations

The ability to process information is fundamental to life. Cells use complex gene regulatory networks to effectively respond to the myriad of signals they receive from both the outside environment and their internal metabolism. This information processing capability enables them to move around, communicate, reproduce - in one word, survive.

Since the early 2000s, researchers have sought to harness this capability by re-engineering cellular signal processing pathways for various biotechnology applications. By implementing rational, controllable logic elements in cells, researchers aim to transform living systems into engineered "machines" that may perform functions ranging from industrial production to biomedical therapies, bioremediation and energy production [1].

Up to date, various strategies and genetic parts have been used to implement information processing systems in cells. Many of these designs use the regulation of DNA expression as the adjustable signal in the circuit. A good example is the “repressilator” built by Elowitz et al. in 2000 that uses three orthogonal repressor-promoter pairs : LacI, tetR and λ cI [2]. Since then, multiple other repressors and activators (zinc-fingers, TALEs) have been used to target specific DNA sequences. Additional recent strategies to engineer synthetic biological circuits include the control of RNA stability, RNA translation or protein-protein interactions as the basis for signal transmission.

The challenge today is to transition from the creation of small genetic “devices” to cells that efficiently perform logical functions that effectively mimic those present in electronic circuits. This challenge calls for innovative strategies and rational design [3]. The engineering-driven approach of synthetic biology, including parts standardization, modular components, modeling and systematic strategies to create biological with reliable and predictable behaviors - holds part of the solution. The other key to the problem is to increase the number of usable orthogonal genetic components for signal processing [4]. The characterization of parts that do not cross-talk with the cellular machinery nor other parts of the genetic circuit promises to improve circuit robustness and efficiency.

Indeed, without orthogonal parts, retroactivity may limit circuit efficiency. Retroactivity involves the risk of downstream genetic elements interfering with upstream ones. Such interference is especially problematic when one tries to connect multiple elements in complex circuits. Retroactivity is not the only limitation of current cell signal processing circuits. To begin with, such circuits are slow : their response time can be measured in hours or even days. Furthermore, such circuits are often unreliable and offer low signal-to-noise ratios. Low output signal may make the connecting of multiple circuits impossible. Another limiting factor is the fact that the transcription factors used as fundamental parts for the circuit may be toxic for the cell and that the circuit itself may monopolize the cell’s resourcer and alter its behaviour. Finally, circuit parts may behave unexpectedly in new genetic contexts [5]. These issues underline the huge task at hand when one dreams of transferring computing from a world of silicon into the realm of biology.

dCas9 to the rescue!

CRISPR stands for Clustered, regularly interspaced, short palindromic repeat arrays. It plays the role of an 'immune system' for bacteria by targeting and degrading foreign DNA. The CRISPR systems uses a Cas9 (CRISPR-associated) nuclease to introduce double-strand breaks to the DNA sequences that are complementary to “guide” RNA (gRNA) [6]. Catalytically “dead” Cas9 (dCas9) lacks the ability to cleave DNA and may act as programmable transcription regulator by either preventing the binding of the RNA polymerase (RNAP) to the targeted DNA - or as an activator when fused to a RNAP recruiting element (the omega (ω) subunit of RNAP in E. Coli and VP64 in Yeast) [7].

The main advantage of this system is that many different orthogonal pairs of synthetic promoters and targeting gRNAs can be designed. In addition, synthetic promoters may be designed in order to have multiple regulating binding sites and thus be able to have multiple inputs, both activating and inhibiting. Since the use of the CRISPR technology to regulate gene expression is relatively new, few logic circuits have been tested with this technique (NOT gates are the most complex circuits reported in the literature) [8]. The challenges with this system are dCas9 toxicity, non-specific targeting of dCas9 and the use of Cas9 as a shared resource for the entire circuit.

However, given the numerous advantages of this system, we decided to attempt to represent binary signals (via transistors) and build logic gates with these two ”elementary” CRISPR/Cas9- dependent operations. We hope hope to demonstrate its viability as a transformative tool to rewire genetic networks.

References

[1] Brophy, J. A., & Voigt, C. A. (2014). Principles of genetic circuit design. Nature methods, 11(5), 508-520.
[2] A Synthetic Oscillatory Network of Transcriptional Regulators; Michael Elowitz and Stanislas Leibler; Nature. 2000 Jan 20;403(6767):335-8.
[3] Purnick, P. E., & Weiss, R. (2009). The second wave of synthetic biology: from modules to systems. Nature reviews Molecular cell biology, 10(6), 410-422.
[4] Bradley, R. W., & Wang, B. (2015). Designer cell signal processing circuits for biotechnology. New biotechnology.
[5] Brophy, J. A., & Voigt, C. A. (2014). Principles of genetic circuit design. Nature methods, 11(5), 508-520.
[6] Sashital, D.G., Wiedenheft, B. & Doudna, J.A. Mechanism of foreign DNA selection in a bacterial adaptive immune system. Mol. Cell 46, 606–615 (2012)
[7] Bikard, D., Jiang, W., Samai, P., Hochschild, A., Zhang, F., & Marraffini, L. A. (2013). Programmable repression and activation of bacterial gene expression using an engineered CRISPR-Cas system. Nucleic acids research, 41(15), 7429-7437.
[8] Qi, L.S. et al. Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression. Cell 152, 1173–1183 (2013).