Researchers from institutions across the United States are contributing to innovative projects at the NSF-Simons National Institute for Theory and Mathematics in Biology. These research
projects focus on developing mathematical frameworks that illuminate emergent capabilities of biological systems. The NSF-Simons NITMB is developing the theory and mathematics needed to highlight the fundamental roles of physical, chemical, and biological constraints as organizing principles for understanding biological mechanisms. In order to highlight the diversity of experts developing NITMB Supported Research and the significance of their contributions, we will share insight into our growing community of researchers as part of the NITMB Spotlight series.
Orlando Arguello-Miranda is an assistant professor in the Department of Plant and Microbial Biology at North Carolina State University. The Miranda Lab works to understand how cells divide, with the goal of discovering new biochemical mechanisms that help cells divide when needed. The lab also wants to learn how cells stop whenever cell division is too dangerous and could result in irreversible cellular damage. Arguello-Miranda is also a contributor to the NITMB-Supported external research project, ‘Equation learning modeling of mitochondrial inheritance during sex cell production’
We spoke with Orlando Arguello-Miranda to learn more about his work with cell division and how collaborating with mathematicians could lead to revolutionary discoveries in biomedicine and agriculture.
What is a big question you’ve been asking throughout your research?
“My research centers around the question of how cells divide and how they make the decision to divide. Most cells will not divide throughout most of their life; but at some point, depending on different internal stimuli and signals from their environment, they decide to divide. This process of whether the cells should divide or not has multiple applications in biomedicine and agriculture. For example, when cells cannot divide, they might fail to create organisms, heal wounds, or to grow. When cells divide too much, they could produce diseases such as cancer. Whether cells divide or not makes the difference in whether a biological process is beneficial or not for humans.”
What disciplines does your research integrate?
"My laboratory tries to bring together different fields, from biomathematics and artificial intelligence to biochemistry, to gain a holistic understanding of the process of cell division. Recently, this really requires methods derived from artificial intelligence, because we are digging into molecular processes that have multiple components and display extreme complexity."
Where do you find inspiration?
"I derive my inspiration from the intrinsic curiosity of the human experience. I also derive
inspiration from seeing students learn. It’s really rewarding to see people start to appreciate
different aspects of human history and human discovery by being exposed to research.
My major inspiration is the potential of all this new information we generate in the laboratory to benefit society and improve the lives of people. I’m always thinking that what we’re doing might positively impact people in 20 years, 50 years, or 100 years from now. It's hard to predict where human societies will go in the future, but we will definitively be better off by gathering more information about how cells divide.”
What aspects of your research could be interesting to mathematicians or applied to biology?
“I would say complexity. The complexity of living systems is an open frontier that is still not
entirely explored. Recently, we have developed new tools to try to gather more information
about single living cells faster. Now we need to process that information and try to make
mathematical and predictive models with those results. At this point we’re full of data from
multiple sources, like new microscopy techniques, new sequencing techniques, new ways to
modify the DNA of organisms. But this data needs to be put in context. That requires a lot of
mathematical approaches. We can only make sense of all this new data with the help of
mathematicians.”
What about the NITMB do you find exciting?
“The fact that NITMB encourages communication between mathematicians and experimentalists to generate new biologically-inspired mathematics. Experimentalists have a lot of data and information that usually remains under-analyzed by mathematical approaches. And I think that enabling communication between people that do experiments and people that do theory is really important because sometimes the people doing the theory have answers to abstract problems, but they don’t know the answers they found actually have very real physical applications in some biological systems, and the other way around. Without
communication, you can have theories and data, but you might not produce scientific discoveries.”
What career achievement are you most proud of?
“If I had to pinpoint one single aspect of it, that would be my transition from biochemistry into the study of artificial intelligence approaches to cell biology. As a result of that, my research is a combination of the two disciplines which has allowed me to created microscopy set ups that record multiple biochemical processes in single living cells cells for long periods. Recently, My lab has developed new approaches to track cells implementing generative AI, and I think that is also going to be a big achievement because it really shows that generative AI could be applied to very fundamental biological problems.”
Outside of your research, what other interests do you have?
“I love Languages and philosophy. I am a big fan of Wittgenstein and philosophers from India, such as Nāgārjuna and Tsongkhapa. I also love the philosophy of language. I’m part of the British Wittgenstein Society. I try to some extent to write a bit of fiction and nonfiction. I would like to be an amateur writer at some point. The subjects I write about are religion, science, and how societies approach the unknown.”
What are you hoping to work on in the future?
“I’m really interested in trying to develop tools to quantify and characterize biological networks. We have the tools and data processing capabilities to image entire biological networks and to try to understand emergent properties in complexity directly from single cell experiments. In the future my laboratory will create new tools and new mathematical frameworks to approach complexity in biology. I hope that’s going to lead to new strategies and understanding of how to control cell division. In the next 25 years, if everything goes well, we’re going to find strategies to reprogram cells to divide on command or to not divide. This could have a lot of applications. For example, if you could prevent cells from dividing and decaying, you will force them into dormancy, also known as quiescence. This could be used, for example, to preserve food. We could also explore why microbial dormant cells are antibiotic resistant and how can we develop antibiotics that target cells that are not dividing. If we could find universal principles that control how cells enter dormancy or enter cell division, I think we will have many impacts in multiple fields.”
Is there anything else you would like the NITMB community to know about you?
“I am the first scientist in my family. I had an interest in science since early childhood. I
always wanted to be part of a team that was doing something really beneficial for humanity.
Coming together with bio-mathematicians, mathematicians, and theoretical scientists, to
discover new biological principles fulfills that dream. I’m glad I can contribute in this way. I’m really grateful for this opportunity.”
More information about Orlando Arguello-Miranda’s work is available on the Miranda Lab website. Orlando Arguello-Miranda also recommends anyone interested in learning more about his work to explore his Google Scholar page to see his recent publications and learn more about the work by reading the editorials published with the articles. Arguello-Miranda also recommends exploring his GitHub page, checking out Python Packages developed with his work, and connecting with him directly through email.