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Melda Tozluoglu tells us about her recent publication in Dev Cell

We've asked Melda Tozluoglu, from the Mao Lab, to tell us about her recent publication in Developmental Cell.


What discoveries have led you to your current work?
When you are thinking about shape changes or movement of a tissue (in fact of anything), there have to be forces and mechanics involved. We know mechanics play a role in biology, but we have only come to appreciate how big that role is in recent years. For cell and tissue shape changes in particular, it has been shown that neighbouring regions of a connected tissue can grow at different rates, and this brings about deformations as the regions try to fit next to each other. We took this idea of heterogeneity in preferred shapes in nearby regions driving cell shape changes and started working on larger scale tissue shape changes.

Why is your research important?
Everyone starts life as flat epithelia; as the embryos grow, these flat sheets fold into functional organs with complex 3D shapes. Beyond the initial body formation, tissue shape can be changed in disease, for instance excessive growth in cancer can cause buckling and folding in tissues, deforming their functional structure. If we understand how complex tissue folds are formed where they are, we can start thinking about generating the shapes we desire artificially, and design interventions when things go wrong. I am a computational biologist, which means I build representations of real tissues on a virtual environment, where we can change everything we want to probe, specifically and thus without any side effects on other properties. We do not have this level of flexibility and precision in real tissues yet. Our computational model allows us to dissect different properties, such as the stiffness or shape of a tissue, and understand the precise influence of each on the final shape.
 
What are you trying to understand?
For the organs to form their 3D shapes, they need to fold from flat epithelial sheets. They not only need to fold, but they need to fold in precise locations for the final shape to be correct and functional. I am trying to understand how a tissue knows where it should fold, especially in situations where you have multiple folds in different shapes next to each other. Our main hypothesis, which turned out to be correct, is that the mechanics arising from the differential growth of nearby regions are sufficient to position the folds correctly.
 
What model system/techniques did you use?
The model system we focus on is the embryonic wing epithelium in fruit flies. This tissue will grow to form the wing, the shoulder and part of the torso of the fly. Main discoveries of the work are driven by computational modelling, a finite element model of the tissue. This involves designing a mathematical model to represent the behaviour of the tissue, building the software to simulate this mathematical model, then running these simulations on high throughput computing servers or university to provide predictions. We use genetic techniques and fixed tissue imaging to first parameterise our computational model, then to validate its predictions.
 
Can you use an analogy to help us understand your work?
The easiest way to visualise why tissue fold positioning is important is to pick up a piece of paper and attempt to fold an origami piece. Although you can follow the instructions, your first crane will probably be all wrong, as you could not fold it precisely. You can restart a crane, but restarting a wing is a bit more challenging for a fly embryo, so the fold positions must be precise from the beginning. Now to see how the folds will form with differential growth, imagine an old sweater, that loosened irregularly. Regardless of how hard you try, it will always look a bit wrinkled. That is because the fabric is still intact, but it is not the same size in different parts, so it has to deform to fit into a “connected sweater”. This is how differential growth can define the fold positions of a tissue. If you take a new-sweater-shaped cardboard and stitched the edges of your old sweater to this rigid board, limiting its overall shape, the wrinkles will become even more visible, this is the confinement brought by the extracellular matrix.
 
What has been your most exciting discovery?
The differential growth of the tissue is enough to give the precise position and shape to the tissue folds, but the folding itself requires the confining effects of the extracellular matrix, a dense polymer mesh that acts as a boundary around the tissue. When we change the growth rates a bit, we predict in the model that tissue will still have folds, but they will be in different positions. Then when we look at animals that have such a change in growth, they have the exact same new shape as we predicted. That second part solidifies it is the growth rates that determine the position. Seeing the images of the real embryonic wing tissue, with exact same deformed structure as I predicted, was one of the most exciting moments of the last 5 years.
 
What’s next?
Now we know that folds can be initiated with differential growth, we can go one step forward and look into feedbacks of how fold initiation can change the mechanics of a tissue, which in turn, will progress the 3D shape changes of it. It is a continuous conversation between mechanics and biochemistry. Now that we have started the conversation, we can continue on to the next stages .

Written by Melda Tozluoglu