SB201 Discussion Questions – Positional Information

How close to the information theoretic optimum within a morphogen gradient do actual
embryos actually come? Imagine scaling of the morphogen gradient across species or between:
maybe the patterning system is actually set up to robustly produce a much smaller number of
domains than would be maximally possible. Would be nice to do some study to compare how
close (maybe introduce some measure of how far away from maximally using the information
the embryos are) different embryos/systems come to reading out the gradient.

Imagine more than one gradient: Mutual information gives you a single covariance measure
between predicted position and a single gradient that satisfies nice information theoretic
constraints (additivity of information, etc.). But in the estimation is sort of locally correlating one
gradient with position and then the next. Maybe on could deploy some maximum entropy
model or other ideas to estimate the joint probability distribution of 2 or more gradients at the
same time to estimate position, and also uncover possible relationships between 2 gradients, ie.
If one was the result of the other.

What are some biological mechanisms by which the computation of positional information by a
cell could be computed? Biologically/molecularly, how does a cell correlate expression of
multiple genes? (Thinking particularly of the example in Fig. 2C) This gets even more complex if
expression isn’t treated as a binary, morphogen present or not present, classification.

As demonstrated by their analysis, the 4 gene system could theoretically provide much more
positional information than it actually does. Why have such redundancy? What happens if the
redundant information sends conflicting signals?

Intuitively, it makes sense to be that it could be some imprecision in the ability of positional
information to identify the location of a given nucleus, but how do you reconcile that with i.e.
cell fate mapping in C. elegans, in which the trajectory of every cell can be determined based on
its location?

In what ways is it surprising a model independent of so many parameters is still accurate? Or
might we actually expect this independence?

Might we see this model hold true in other species? Is there any research to this end?

What might be some ideal experiments to test whether their claim about relative positioning
over absolute positioning holds true?

In the end the authors didn’t use the gene expression profiles to generate positional information
that suggest the fate of each nuclear, so what is the importance of all these calculations?

Why is the redundancy small at the level of pairs and high at the level of gene quadruplet?

Are there situations in which their system breaks down, even when expression is at steady
state? (this fairly newly-discovered form of morphogen transport comes to mind
http://www.sciencedirect.com.ezpprod1.hul.harvard.edu/science/article/pii/S0959437X14000203 “Specialized filopodia: at the
‘tip’ of morphogen transport and vertebrate tissue patterning”)

What other systems seem especially suitable for this kind of analysis?

They find that the tendency of a nucleus to erroneously switch identities with its neighbor is
~16% in this stage of drosophila development given their calculated positional error of ~1%. Is
there experimental evidence for this? (I know in some of Sean’s videos it seems apparent that
some cells are out of place and then must move into the proper positions… could this
erroneous neighbor switching be the cause for what is seen in Sean’s microscopy?)
SB201 Discussion Questions – Symmetry breaking

How many domains can you get? Are there any triple stable systems out there in nature, where
spatial segregation could create 2 different domains? How does this system differ from Jim
Ferrel’s mitotic trigger waves where he wants a stable steady state to propagate over space
faster than diffusion? How exactly do you prevent Jim Ferrel’s system from getting patchy cdk1
activation? Can they get in this study lack of 2 stable local patches if you tune some
parameteres?

How do you robustly control the protein levels in natural C elegans to get 2 domains? How much
variation is there? What are the mechanisms for the control of the limiting protein pools
controlling domain size?

How do you control advection? Do you need advection in any particular region to get this
process started? Is it random?

Why is this symmetry breaking so different to other organisms? Is it different at all?

Both of the reviews compares advection to transport of objects in a flowing river, but is that the
best analogy? Rivers have definitive upstream and downstream directions, where it seems to
me that the direction of advection in the context of the paper is more random than that. But
the point about large objects following flow forces while small particles diffuse too quickly and
do not flow makes sense.

Much of their evidence is based on being able to make a model that matches what is observed
in the embryo. Is there a more direct way to measure the flows?

Now that we’ve studied both phenomena, albeit out of order, what is the distinction between
symmetry breaking and initial axis specification?

How do these different poles interact with one another in a cell?

In developing animal cells, are there any symmetry breaking patterns that occur with greater
likelihood—is one species’ cells more likely to develop via a specific pathway than another
species? Or is it all random determination of which pathway a new cell utilizes, so long as some
asymmetry occurs?

What about the pathways themselves might make one ideal (or more likely) for a given
environment? Does one pathway lend itself as the best option under certain conditions not
intrinsic to the cell?

The amount of aPARs is unlikely to be limiting since aPARs initially cover the entire cell
membrane. Is there any change in the concentration of aPARs before and after polarization?

Is the direction of the fluid flow consistent among cells and why?

What is upstream signal that triggers polarity?

How do these different poles interact with one another in a cell?

In developing animal cells, are there any symmetry breaking patterns that occur with greater
likelihood—is one species’ cells more likely to develop via a specific pathway than another
species? Or is it all random determination of which pathway a new cell utilizes, so long as some
asymmetry occurs?

What about the pathways themselves might make one ideal (or more likely) for a given
environment? Does one pathway lend itself as the best option under certain conditions not
intrinsic to the cell?

Are there other clear examples in which passive diffusion can be the catalyst of polarization?

Do differences exist in the susceptibility of aPARs and pPARs to be affected by advection?
Although this is only important as long as fluid flow is occurring, it seems it could further amplify
or speed up the polarization process. (hypothetically, say aPARs are very much affected by
advection while pPARs generally just stay in place… this would further decrease the aPAR
concentration at the posterior end… this may have been mentioned and I simply missed it, but I
don’t remember reading anything specifically about this situation)

Is it possible that this polarization is also maintained by anti-correlated concentrations of factors
that promote one type of PAR proteins but inhibit the other? Conceptually, could something like
this give domain boundaries as sharp as ones generated by antagonistic behavior between the
aPARs and pPARs? It seems like this would also create polarization but might lead to a sort of
fuzzy boundary… are there examples of this?