A quick briefing on Notch activation

Mature Notch receptors are cleaved at a S1 in the negative regulatory region (NRR) heterodimerization domain during its delivery to cell membrane. A currently widely accepted model of Notch activation begins as the receptor’s ectodomain binds to ligands on sender cells with high affinity. The Notch core is then "opened up" at its negative regulatory region (NRR) by the mechanical force exerted by Notch-bound ligand endocytosis process on signal-sender cell, exposing its cleavage sites to proteases ADAM10/17 and Gamma secretase, releasing the Notch intracellular domain (NICD). In the majority of cellular interactions, the free Notch intracellular domain then translocate into the cell nucleus via nuclear localization sequence to regulate downstream signaling. For wild type Notch, the Notch intracellular domain would interacted with its major downstream effector CBF-1/Suppressor of Hairless/Lag-1) (CSL) on their target DNA. Together they recruit co-factors to activate endogenous downstream transcription. For SynNotch, specialized factors will exclusively participate in regulation of genetic circuits that allow user-defined cellular responses. n our project, from Dry lab results as well as Wet lab results, we realized that high functioning SynNotch receptors with high signal-to-noise ratio is its cornerstone. (See reference in Antigen, receptors page.)

So, in this section, we refer to the structural information from former very clarifying structural research on human Notch 1 and human Notch 2 receptors for their striking similarity to try to optimize the mouse Notch 1 receptor core for better performance of the SynNotch in our project. Through truncations and point mutations of the negative regulatory region (NRR), we have attained some results and characterization with better signal-to-noise ratio, though there is still a long way to go.

Notch core optimization

SynNotch and surface antigen (surAg)

For our project’s Wet lab part, we first built a variety of SynNotch with the same synthetic intracellular domains (SynICDs), but has different synthetic extracellular domains (SynECDs). We chose three different Synthetic extracellular domains: LaG17 (low affinity single domain antibody against EGFP), LaG16-2 (high affinity scFv against EGFP) (Fridy PC, et al., 2014), αCD19 (scFv against CD19) (Grupp SA, et al., 2013) with same SynICD: tTAA (tTA-Advanced. Its corresponding promoter is TRE3GV) which can theoretically respond to surface EGFP (surEGFP) and surface CD19 (surCD19), as summarized in Table 1.

We first propose a simple way of measuring the performance of SynNotch activation with:

MFI_EGFP: Mean fluorescence intensity (MFI) of 293T cells activated and expressing EGFP as signal output of SynNotch activation in flow cytometry

Freq_EGFP++: Frequency of EGFP positive cells in parent cell population, in other words the percentage of cells that has SynNotch activated

MFI_mCherry: Mean fluorescence intensity of mCherry fluorescence internal control.

SynNotch and surAg are delivered onto cell membrane

The activation of SynNotch is dependent on cell-cell contact between ligand and receptor. In order to verify the function of SynNotch, the first thing we need to know is whether the protein and its corresponding surAg are expressed outside the cell membrane. We used immunofluorescence to verified the surface-EGFP (surEGFP), surface-CD19 (surEGFP) and LaG16-2-SynNotch are indeed expressed on the cell membrane. The sharp fluorescence outline confirms that these proteins are expressed outside of the membrane (Figure 1). Since LaG17 and LaG16-2 are similar in function, we did not test the membrane expression of LaG17. For αCD19-SynNotch, we tried another method by using flow cytometry staining. The αCD19-SynNotch cell shows a positive population comparing to the negative control. Overall, we confirmed that all of surEGFP, surCD19, anti-EGFP-, anti-CD19-SynNotch express on the membrane.

Comparison of activation between different types of SynNotch with the same intracellular domain

Considering the inherent limited number of intracellular domains that will enter the cell nucleus and the range of output theoretically needed for our Amplifier layer, we chose the mouse Notch core as the foundation of our Receptor layer.

Mouse Notch core is highly similar in amino acid sequence to human Notch core. Therefore, in this study, even though we do not have information on the exact structure of the mouse Notch NRR domain, we referred to human Notch 1 and 2 receptors’ NRR structures deciphered by Gordon and her colleagues in the past few years.

On the basis of the mouse Notch core, we furthered compared the performance of SynNotch with different scFv (single chain variable fragment). The basal activation of anti-CD19 is the lowest compared to LaG16 -2 and LaG17, and it also has a moderate activation performance, making it the SynNotch with the highest signal-to-noise ratio. On the contrary, we found that although the activation rate of LaG17 SynNotch is the highest, so is its basal activation, making it the SynNotch with the lowest signal-to-noise ratio (Figure 3b). SynNotch with the same NECD but different NICD comparison shows that SynNotch with tTAA is highly functionging, while SynNotch with Gal4-VP64 NICD shows poorer acitivity. Therefore, it indicates that choice of the extracellular domain as well as intracellular domain can influence SynNotch performance although the Notch core, which includes the protective negative regulatory region and transmembrane region, and the intracellular domain are the same.

Hence, we chose LaG17 SynNotch with the mouse core and tTAA NICD that demonstrates high sensitivity but also high basal activation for optimization.

Exploring multiple truncation of the LNR-A domain in the Notch core

Although Notch mutations has been associated with T-cell acute lymphocytic leukemia (T-ALL) and developmental disorders (Ferrando A., 2010; Gordon WR, et al., 2009; Mansour MR, et al., 2006), the optimization of SynNotch is conducted with the goal of adding to the characterization of the Notch core and SynNotch from a preliminary structural perspective in order to use it as a well-defined tool in synthetic biology in the future.

Consistent with past studies that removed the lin12-repeats (LNR) (Sanchez-Irizarry C, et al., 2004; Gordon WR, et al., 2007; Greenwald I, et al., 1990), deleting the LNR-A region in its entirety as well as deleting it with the LNR-AB linker that protects the S2 cleavage site both can lead to higher activation of SynNotch. This also seems to cause irregular activation activity. Of course, more repeats are needed for further verification. However, when the last helix of the LNR-A domain remains and the rest of it is deleted, there is a significant decrease in activation compared to the former two truncated versions, even slightly lower than intact Notch core. This is inconsistent with former studies that proposed LNR-A as a blockage against ADAM 10/17 metalloproteases to prevent premature activation via S2 site, smaller LNR-A domain might render easier activation of Notch, not harder. Further verification needs to be done.

Addition of flexible glycine linker between the truncated NRR LNR-A domain and scFv can make up for the deletion to an extent

From what we saw in Figure 1b where SynNotch with different ectodomains would exhibit differed activity, and from the truncation results, guided by implications from past research in NRR mechanism and ADAM10/17 (Seegar TCM, et al., 2017), it occurred to us that the steric hinderance of NECD would influence Notch cleavage, therefore adding residues back might lower the basal activation or lower induced activation.

From the results from Figure 4, it seems as if there is a threshold length or structural hinderance of LNR-A that is within the range of optimal enzymatic activity for ADAM10/17 cleavage. Of course, further experiments must be done to rule out possibilities of SynNotch malfunction.

Mutating the calcium binding site of LNR-A and LNR-AB linker for better SynNotch receptors, some of them showing improvement

Studies have shown that calcium depletion of the negative regulatory region (Gordon et al., 2009a and Gordon et al., 2009b; Rand MD, et al., 2000) could activate Notch, implying the electrostatic interactions of calcium ions with LNR domains and heterodimerization domain are fundamental in holding the NRR together. It occurred to us that perhaps slightly maneuvering the interaction strength by changing neighboring side chains of amino acids could either lead to either high basal activation with higher sensitivity, or lower basal activation with same or lower activation. We first analyzed the how conserved these amino acids are and chose ones that are quite conserved. Mutating the amino acids into others with residues with diverged features, we found that changing the charge from negative to positive (Lysine, K) significantly sensitized SyNotch.

Similarly, we learnt from Gordon’s work in 2007 and 2009 that both natural Notch 1 and 2 heterodimerization domains contain a hydrophobic pocket that is plugged by a highly conserved Leucine, and the two amino acids in close proximity seems to help to hold the “plug” in place. Therefore, either changing the residue to more hydrophilic ones would lead to higher basal and induced activation, or changing it to hydrophobic ones might have the opposite result. In addition, the hinderance sterically exerted by amino acids with larger side chains might either make it “unpluggable”, or and amino acids with smaller side chains might make it “unplugged” with little mechanical force.

Analyzing the results, it seems more likely that the size of side chains plays a significant role. Mutating Leucine to Valine and Glycine or Alanine is downsizing the side chains. So, the LNR-AB linker might be easier to pull out and give way to ADAM10/17 proteolysis.

To find out if the same principle would apply to LaG16-2 SynNotch and anti-CD19 SynNotch, we did the leucine mutation on them. We didn’t have the time to finish and do more repeats to verify, but luckily mutated LaG16-2 SynNotch are still well functioning.

Conclusion

Through carefully designed experiments, we have attained D1433K, D1433Q, L1457V, and L1457G (for mouse) mutations for LaG17-mNc-tTAA SynNotch optimization. Of course, we still need more experimental repeats to further verify their validity.