Small Cell, Big Picture: Fundamental Biology Through the Lens of Simplified Models

The nucleus of a cell may only be one-thousandth of a centimeter in diameter, but that doesn’t stop biophysicist Alex Rautu from seeing the big picture.

Alex Rautu is a Flatiron Research Fellow at the Center for Compuational Biology. Credit: John Smock

Alex Rautu doesn’t have the problem of not seeing the forest for the trees — or, in his case, not seeing the workings of a cell’s nucleus for the movement of its molecular machines.

At the Flatiron Institute, Rautu uses mathematical models guided by active matter physics to understand the mechanics and dynamics of the nucleus. Where biologists often look at the details, Rautu looks at the big picture to see how tiny enzymes and molecular motors can have such a big influence on the movement of material in this cellular compartment.

Though he is a physicist by training, this is not Rautu’s first foray into biology. Over the years, his research has taken him on a journey through the cell and around the world. During his doctoral studies at the University of Warwick in the U.K., he focused on lipid membranes, which form the boundaries of cells. As a postdoctoral researcher at the National Centre for Biological Sciences in Bangalore, India, Rautu studied the cell itself, seeking to understand how both fusion and fission of membrane material control the dynamics and composition of subcellular organelles. Since 2020, Rautu has been a Flatiron Research Fellow at the Center for Computational Biology (CCB) investigating the nucleus of the cell.

Rautu recently spoke to the Simons Foundation about his work and the importance of looking at the big picture. The conversation has been edited for clarity.


What is active matter physics?

Active matter physics is an emerging field in the larger discipline of soft matter physics. Soft matter physics describes soft materials, like polymers and biological materials, which are easy to deform, as opposed to things like crystals or glasses, which are rigid. Within soft matter, there are systems that have ‘active agents,’ meaning things that consume energy in order to perform mechanical work. Bacteria are an example of such active agents. Unlike, say, atoms, which move passively, bacteria can propel themselves. This activity can lead to emergent collective behaviors, like flocking together or clustering to form a bacterial colony, which manifest at scales much larger than an individual bacterium. In essence, the governing motion of many constituents is thus different to that of an individual in isolation, and their activity can often have surprising results.

Active matter physics can also help us to understand the governing physics of organelles within a cell, which is what I study. By using the principles of active matter, I aim to understand the dynamics and functions of cellular components and gain a deeper understanding of their role in the overall functioning of a cell. My research centers on investigating the interactions between fluids, enzymes and molecular motors in order to gain insight into how they move and transport within the cell. This often involves a combination of various branches of physics, including chemical reactions, thermodynamics and hydrodynamics. These concepts are crucial in understanding the subcellular processes such as the transport of proteins and other biochemical reactions that are fundamental to the survival of the cell. Understanding these underlying physical principles may enable researchers to gain insights into how to improve biotechnology and medical treatments that involve subcellular processes.


How do you apply active matter physics to your work at the Flatiron Institute?

Currently I’m working with CCB director Michael Shelley to study the nucleus. This is the part of the cell that contains the DNA. Proper organization of DNA in the nucleus through its packaging and structure is essential for the proper regulation of gene expression, which in turn ensures the normal functioning of the cell. We’re studying which mechanical properties are involved in the organizing of the DNA, which is largely driven by various proteins and enzymes in the nucleus. Individual enzymes produce forces by binding to proteins, causing them to deform and push surrounding fluid out of the way. To gain insight into the overall collective movement of the system, we study the mechanical properties of the entire nucleus, rather than examining the DNA or enzymes in isolation.

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By using a hydrodynamic model, Rautu and his collaborators investigated the dynamics of chromatin, the material that composes the nucleus of cells and contains DNA. They modeled chromatin as a fluid that is both viscous and compressible, allowing them to simulate the properties of heterochromatin, a specific type of chromatin known for its tightly packed structure and the presence of contractile stresses caused by crosslinking proteins. These stresses can lead to density instabilities and large-scale flows. This simulation revealed the initial formation of heterochromatin droplets, followed by their redistribution at the nuclear periphery. This research offers new understanding into the mechanical processes that govern the spatial organization of heterochromatin. Credit: Alex Rautu

This research addresses fundamental physics questions by examining the basic forces at play within a cell. By using mathematical models, we aim to understand how these forces influence the organization of DNA within the nucleus.

While biologists often focus on studying small, specific details to gain insight into how a particular system works, in some cases it is important to also take a step back and consider the larger picture. By studying the mechanical properties of the nucleus as a whole, we can gain a deeper understanding of the fundamental principles governing the behavior of biological systems. The beauty of this approach is that it allows us to identify patterns and connections that might not be apparent when studying individual components in isolation.


How does mathematical modeling help you see the big picture?

Just as you wouldn’t study individual atoms if you wanted to understand which way the wind was blowing, we’re not looking at individual molecular motors or proteins. Mathematical modeling helps us understand the systems we study as a whole, without getting hindered by the details. The key features of interest are more apparent when viewed from a larger perspective, only visible if you zoom out.

In this work I generally start with a reduced model that consists of a set of partial differential equations to describe how a system changes over time and in space. On long timescales, the nuclear constituents behave like a viscous fluid, albeit a compressible fluid, which is one where the fluid’s density changes over time. Our equations reflect how this compressible fluid changes and flows.

To write these equations, we start with basic principles to create a simple model of what’s going on in the system. This approach is similar to how you might study crowd dynamics. Say you wanted to know how a group of people would leave a crowded music venue. First you would write out equations that describe how people walk, and then you would add in rules — like that people can’t walk through each other or through walls. By solving these equations, you could then predict the overall movement — or flow — of people out an exit door. We’re doing the same thing here with the fluid in a nucleus. Instead of humans, we’re modeling the fluid, but we still have similar rules. In this case, our rules are things like conservation of mass and momentum.

Once we develop a reduced model, we can add in other factors. For example, if we introduce equations to describe chemistry, we can understand how things react and how that reaction affects other parts of the nucleus. Each additional element that is incorporated into the model enhances our understanding of the system as a whole. Even though the actual system is vastly more complex, studying reduced models still holds great value in advancing our understanding of the nucleus.