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  <title><![CDATA[PhD Defense by Pedro Marquez Zacarias ]]></title>
  <body><![CDATA[<p>In partial fulfillment of the requirements for the degree of Doctor of Philosophy in Quantitative&nbsp;<br />
Biosciences<br />
in the School of Biological Sciences</p>

<p>Pedro Marquez Zacarias</p>

<p>Defends his thesis:<br />
Title: Life cycles and nascent multicellularity</p>

<p>Wednesday, August 17, 2022 3:30pm Eastern Time<br />
https://gatech.zoom.us/j/97899556958 Open to the Community<br />
Advisor:<br />
William Ratcliff (School of Biological Sciences, Georgia Tech)<br />
Committee Members:<br />
Peter Yunker (School of Physics, Georgia Tech)<br />
Samuel Brown (School of Biological Sciences, Georgia Tech)<br />
Eric Smith (Earth-Life Science Institute at Tokyo Tech, and Santa Fe Institute) David Murrugarra&nbsp;<br />
(Department of Mathematics, University of Kentucky)<br />
Abstract:<br />
Life is organized hierarchically. From cells to societies, the levels of biological organization&nbsp;<br />
shape evolutionary trajectories. These hierarchies are traditionally studied through the lens of&nbsp;<br />
the Major Evolutionary Transitions (MET) framework. One such major transition is the evolution of&nbsp;<br />
multicellularity, which gave rise to the evolution of complex life forms like animals, plants, and&nbsp;<br />
fungi.<br />
First, I will discuss how multicellular organisms differ in their ecology and evolutionary&nbsp;<br />
trajectories, particularly depending on whether they develop via aggregation (cells coming&nbsp;<br />
together) or by clonal development (cells staying together). This will lead up to a more general&nbsp;<br />
question about life cycles, and how are these organized differently in multicellular organisms&nbsp;<br />
compared to their unicellular counterparts. To give clarity on this matter, I developed a&nbsp;<br />
compositional algebra to serve as a formal language to represent and analyze life cycles of&nbsp;<br />
arbitrary complexity. With this algebra, I was able to describe the life cycles of complex and&nbsp;<br />
simple multicellular organisms and found that organisms that develop via aggregation are more&nbsp;<br />
similar to unicellular organisms than even simple multicellular organisms. I provide some criteria&nbsp;<br />
to distinguish between hierarchical levels of reproduction, which I<br />
distinguish from the levels in MET by the features of their life cycles.</p>

<p>Then, I present a simple model of clonal multicellular development that explicitly accounts for&nbsp;<br />
spatial constraints. In this model, cells have a specific pattern of cell division that can account&nbsp;<br />
for simple morphological features observed in nascent multicellular organisms. Using this model, I&nbsp;<br />
was able to directly query the effects of aspect ratio and lateral cell growth, or &lsquo;side-budding&rsquo;.&nbsp;<br />
These are two traits known to be important for organismal size in snowflake yeast, which is the&nbsp;<br />
experimental system we use in the lab to study multicellular evolution. Further, I show how simple&nbsp;<br />
genetic disruptions to the machinery that controls the patterns of growth in single cell yeast can&nbsp;<br />
have important effects when applied to snowflake yeast.<br />
Finally, I present a novel method to measure spatial structure in biofilms, which leverages methods&nbsp;<br />
and concepts from network theory. This method relies on the network representation of a biofilm,&nbsp;<br />
which gives us flexibility and scalability while preserving as much detail as needed. I show how&nbsp;<br />
this method is applied to real data, by analyzing microbial communities with cooperative or&nbsp;<br />
competitive interactions, and showing the detailed spatial information recovered with the proposed&nbsp;<br />
method.<br />
Altogether, in my thesis work I explored the theme of biological organization: the organization of&nbsp;<br />
life cycles, the morphological organization of simple multicellularity, and the spatial&nbsp;<br />
organization of<br />
microbial communities.<br />
&nbsp;</p>
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