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Brewster Lab @brewsterlab.bsky.social · 17/12/2024

There's more in the paper, but here is an overarching figure. All the data from the paper (and some existing data) collapsed to the same basic, universal behavior. We never see evidence of the relationships that would come from "destabilizing" type interactions. Everything looks stabilizing.

We plot all our data as well as some existing, external data (1000s of data points) on the same collapsed data curve. The collapse is an indicator of a single, conserved mechanism at play in all of the regulatory interactions we study here.

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Brewster Lab @brewsterlab.bsky.social · 17/12/2024

We look at natural promoters. SoxS regulates three promoters (PoxB, FldA and DecR) at very similar positions. The same relationship is visible here covering all the way from 100-fold activation to 2-fold repression, all predictable from the basal activity of the promoter being regulated.

Natural SoxS regulated promoters poxBp, fldAp and decRp have drastically different levels of fold-change exerted by SoxS. This can be shown to conform to the same "stabilizing" relationship, their differences are explainable by their constitutive activities.

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Brewster Lab @brewsterlab.bsky.social · 17/12/2024

We also made a toy system using sigma28 promoters and controlling sigma28 concentration to change promoter activity. Really it's the same story over again. We can change promoter sequence, we can change active polymerase concentration and we see the same signatures of stabilization.

We also build a system using the alternative sigma factor, sigma28, where we can change both polymerase availability (via sigma28 concentration) and promoter sequence. We find, once again, that LacI and CpxR function has the same relationship.

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Brewster Lab @brewsterlab.bsky.social · 17/12/2024

There's other ways to change promoter activity. We alter physiology with media: changing the growth rate changes the activity of each promoter. Here's the LacI and CpxR library. We find the same relationship. The slope across genetics (promoters) and/or physiology (different media) is -1.

We do the same experiment with our 96 promoters grown in different carbon sources. This alters the growth rate and thus the constitutive expression levels of each promoter. However, each promoter has the same "compensatory" stabilizing relationship.

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Brewster Lab @brewsterlab.bsky.social · 17/12/2024

Necessarily, what I mentioned previously is also true. Different promoters with ~100s fold differences in basal expression all produce the same level of regulated expression and that level is different for different TFs. This is very... useful? The expression of each promoter is set by the TF.

It can be demonstrated that this means that this library of promoters all have very similar regulated levels even as the promoters differ in basal expression by 100 fold or so. Here we show this for a repressor (LacI) and an activator (CpxR).

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Brewster Lab @brewsterlab.bsky.social · 17/12/2024

Here's five repressors: LacI, AscG, AcrR, MngR, PdhR. All of them have the relationship expected from a stabilizing TF, including LacI. This is surprising, especially given the standard textbook-level picture of these regulators as steric hindrance machines, interfering with RNAP binding (destab).

Repressors also conform well to the theory predictions for stabilizing TFs.

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Brewster Lab @brewsterlab.bsky.social · 17/12/2024

Here's three activators: CpxR, MetR, SoxS. They all have the expected relationship for stabilizing TFs. It's probably fair to say this is expected. As previously mentioned, activators often work through a mechanism involving a positive interaction between TF and RNAP at the promoter.

Three activators all conform to the predictions for stabilizing TFs.

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Brewster Lab @brewsterlab.bsky.social · 17/12/2024

Our goal was to test this systematically. We used our Titration library (PMC9189660) to measure individual TFs regulating ~100 mutant promoters, measuring both unregulated expression and the maximum regulated expression of each promoter. We plot fold-change vs constitutive exp of each promoter.

We create 96 promoter mutants and calculate the fold-change of each promoter and plot that against each promoters constitutive expression level (delta TF).

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Brewster Lab @brewsterlab.bsky.social · 17/12/2024

Another prediction: the slope for stabilizers is always the same for strong promoters, -1. Here, changing constitutive levels wont change regulated levels. The TF buffers constitutive expression changes of the promoter. However, destabilizing TFs should amplify differences of similar promoters.

An interesting feature of stabilizing TFs is a prediction that they should regulate different promoters such that the regulated level is exactly the same, even as the promoters basal level changes.

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Brewster Lab @brewsterlab.bsky.social · 17/12/2024

Our model predicts a relationship between promoter strength & regulation that depends only on the nature of a TFs stabilizing interactions: Stabilizers will exert lower fold-change on stronger promoters. Destabilizers, the opposite. So CpxR is a stabilizer? We previously inferred that (PMC8667592)

For TFs that act through stabilization, the fold-change decreases as the promoter gets stronger. For destabilizers, the opposite is true.

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Brewster Lab @brewsterlab.bsky.social · 17/12/2024

Stabilization is associated with activators making beneficial contacts with a domain on the RNAP. Destabilization is associated with repressors and "steric hindrance", i.e. exclusionary binding of TF that prevents RNAP from binding partly or fully. Example figures from Lloyd et al PMID: 11758454.

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Brewster Lab @brewsterlab.bsky.social · 17/12/2024

Let's focus quickly on "stabilization". This is the degree to which the TF promotes (stabilizes) or interferes with (destabilizes) the occupancy of RNAP at the promoter. Here we quantify it with the parameter beta, which is really just a measure of how much the TF impacts the TF-RNAP cobound state.

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Brewster Lab @brewsterlab.bsky.social · 17/12/2024

It is also helpful to ask "What were we expecting?" We use a simple model of regulation by two distinct mechanisms: the first (stabilization/destabilization) is the interaction between TF and RNAP at the promoter, the second is acceleration/deceleration of RNAP initiation from cobound TF-RNAP.

Our model considers two modes of regulatory interactions. From this we can calculate the expected fold-change and we find that only stabilization/destabilization interactions at the promoter influence the expected relationship between promoter strength and fold-change.

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Brewster Lab @brewsterlab.bsky.social · 17/12/2024

We tend to excuse these differences as "context dependent" but here context is largely controlled. Is this "context" or rather just a natural characteristic of TF function? Looking at the three promoters above, the two "weak" promoters were activated by CpxR and the "strong" one repressed.

ldtC and yccA promoter are expressed ~100-fold lower than efeU constitutively.

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Brewster Lab @brewsterlab.bsky.social · 17/12/2024

How does a TFs function depend on the promoter it regulates? We know that a TF can have different effects on different promoters. For example, consider this case: CpxR regulates ldtCp, yccAp, efeUp at a similar location. Yet two of them are activated, one repressed #GeneReg 🧪 tinyurl.com/3hr9njnd

CpxR regulates yccA and ldtC as an activator and efeU as a repressor despite binding in a similar relative position on these promoters.

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