Biology

The Art Of Theoretical Biology: how to explain science with art

By Ilaria Terenzi 14 September 2020

Images are one of the best means to celebrate the beauty of science and to explore any biological topic. Computational science and advanced tools highlight basic cell functions, the darkness of disease, environmental questions and – as the editors explain – how complexity generates richness in unexpected ways.

The Art of Theoretical Biology is a collection of pieces of art; they are the result of a deep scientific research, of data analysis and mathematical models; and they may help us make science more accessible to the public as well.

More than 120 authors contributed to this book, creating a synergic union between art and science: a promising new way to show how the potential of mathematical models may support discoveries in any field.

We had the honour and the pleasure to interview the editors of this book: Franziska Matthäus, Giersch Professor of Bioinformatics at the Goethe University, Frankfurt; Sebastian Matthäus, founder and head at the Grenfarben Agentur für Gestaltung, Berlin; Sarah Anne Harris, Associate Professor of Biological Physics at the University of Leeds; Thomas Hillen, Professor and Associate Chair Research at the Department of Mathematical and Statistical Sciences at the University of Alberta.

Cellular Swarms in Cellular Automata by Andreas Deutsch. The Art of Theoretical Biology, p. 105. © 2020 Springer

1) In the preface, it is explained that you conceive “the book as a superposition of art and science; each separate image is an act of scientific research, but the whole collection is a work of art”. From an educational point of view, do you think it would be possible to profit from the conjoined usage of art and science to get closer to the audience?

Yes, our intention was to use the power of images to reach out to non-scientists and increase awareness of and interest in the increasingly important field of theoretical biology. The stories behind each image are formulated in a very compact style free of scientific jargon, and targeted to a wider audience using the scientists’ own words. While most people outside the scientific community would not, out of plain intrinsic interest, read scientific articles, they are nonetheless attracted to the images and become curious, especially because for most of the images it is not immediately apparent what is displayed. Connecting the images to the research story and the creation process allows the reader a short journey into a variety of exciting research topics. We hope that our book will show readers that science is exciting and full of beauty.

2. A significant part of the book concerns oncological research, for the purpose of improving patient treatment and decreasing cancer mortality rates. What are the future perspectives of predictive studies on carcinogenesis by means of mathematical models?

Oncological research profits from a tight collaboration between medics, biologists and mathematical modelers. Validating our predictive models against experimental data can be far more challenging than for inanimate matter. Cancer occurs in living organisms, which are extremely complex and need to be treated with particular care. However, tissue engineers can now grow “tumoroids”, which are synthetic cell cultures that grow into tumor-like tissue, and which can then be studied in a more controlled manner. These synthetic systems are likely to accelerate our understanding of how best to model carcinogenesis.

Moreover, the advent of new technologies such as automated image processing (e.g. of biopsies and scans) and artificial intelligence have generated large interest from the clinical sciences, so increasingly both data science and mathematical modelling are informing medical research and treatment of disease. The future of cancer therapy is likely to be “personalized” or “precision medicine”, where each patient receives a treatment bespoke to their particular disease, which may be based on the genetic profile of their tumour. An exciting example where mathematical modelling is at the forefront of development in precision medicine is adaptive evolutionary therapies. These can drastically reduce side effects, reduce chemotherapeutic resistance and improve patients’ quality of life.

Art Theoretical Biology — Crop Circles of Cancer by Katharina Baum, Jagath C. Rajapakse & Francisco Azuaje. The Art of Theoretical Biology, p. 73. © 2020 Springer

3. Mathematical models may be used in order to develop drugs and to simulate their pharmacokinetics. Thanks to this approach, what progress has been made as regards pharmacological drug development?

For pharmacokinetics, there has been a great deal of progress in the use of pre-clinical models to predict the behavior of drugs in patients in relation to their duration of action, absorption, metabolism, excretion and toxicity. These models use experiments that expose cultured cells and or microsomes (which are highly simplified mimics of organs) to the drug in the laboratory to predict how it will behave in animals.

However, de novo drug design from the molecular level upwards is a very complicated and expensive process. Big pharma companies have recognized the value in computer aided design in optimizing new molecules for further development. However, the enormous complexity of drug interactions, which includes practical details such as solubility and bioavailability, cell penetration, off-target interactions that cause side effects, potential degradation by metabolic enzymes and time to excretion mean that multiple different types of models must be used, depending on aspect of drug development that is being optimized.

4. At present, how determining has been the contribution of theoretical biology to the scientific research? How important is its predictive purpose, in order to improve quality?

The ultimate aim of theoretical biology is to understand living systems, to be able to make predictions about their behavior and to give us the insight we need to engineer them. Models have been used successfully to describe biology at every length-scale, from the movement of electrons during photosynthesis at the sub-atomic level, through to the atomic interactions that drive protein-protein interactions (Knitting Proteins by Santiago Schnell) and molecular signaling cascades (Crop Circles of Cancer by Katharina Baum, Jagath C. Rajapakse & Francisco Azuaje), up to cell dynamics (Cellular Swarms in Cellular Automata by Andreas Deutsch), the biomechanics of organs, and eventually ecological interactions of populations and their response to their environments (Tower of Life by Sylvain Gretchko).

However, what our models are not yet able to do, is to cross these different theoretical regimes. While we can successfully build models at individual length-scales, e.g. for single proteins, or for collections of cells, or for the heart, or the population of a species, we cannot predict how a change at any one of these length-scales will impact the others. For example, when clinical geneticists sequence the genomes of their patients to understand the origin of their disease, they find many “variants of unknown significance”. Genetic variation is so prevalent that it is often impossible to identify the mutations responsible for a genetic disease. While we can say precisely how a mutation will affect the atomic structure of DNA, we cannot predict how this atomic level change will affect the next length-scales up, such as cells or tissues. A major breakthrough in theoretical biology will be when we can trace the information flow between the multi-length scales, so from atomic level changes through to cells and organs, that are all important in biology.

To understand, predict and control a biological system is the ultimate goal of theoretical biology. Scientific merit is measured directly through its implication on science, biology, ecology, or medicine. Theoretical biology is developing fast, many aspects of the experimental data lack reproducibility, because we don’t understand the variables. Models can help with this.

5. The field of theoretical biology also contributes to the study of nature and of environmental impact assessments. Habitat alterations of several species are one of the main anthropic threats to biodiversity. What potential have mathematical tools in the field of ecological issues?

Theoretical biology plays a major role in ecology. Modelling is used to manage fishing quotas, to design protective marine areas, and to control invasive species, such as mountain pine beetles in Western Canada. Modelling is the only way to address vital questions about the future of our planet, such as looming species extinctions and the effect on predator-prey dynamics, biodiversity, evolution. Models enable us to make predictions about the impact of climate change, and to provide scientific strategies to mitigate against the consequences.

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Biology

Why are plants green?

By ScientifiCult 1 July 2020

Why are plants green?

UC Riverside-led research team’s model to explain photosynthesis lays out the next challenging phase of research on how green plants transform light energy into chemical energy

When sunlight shining on a leaf changes rapidly, plants must protect themselves from the ensuing sudden surges of solar energy. To cope with these changes, photosynthetic organisms — from plants to bacteria — have developed numerous tactics. Scientists have been unable, however, to identify the underlying design principle.

An international team of scientists, led by physicist Nathaniel M. Gabor at the University of California, Riverside, has now constructed a model that reproduces a general feature of photosynthetic light harvesting, observed across many photosynthetic organisms.

Nathaniel Gabor is an associate professor of physics at UC Riverside. Credits: CIFAR

Light harvesting is the collection of solar energy by protein-bound chlorophyll molecules. In photosynthesis — the process by which green plants and some other organisms use sunlight to synthesize foods from carbon dioxide and water — light energy harvesting begins with sunlight absorption.

The researchers’ model borrows ideas from the science of complex networks, a field of study that explores efficient operation in cellphone networks, brains, and the power grid. The model describes a simple network that is able to input light of two different colors, yet output a steady rate of solar power. This unusual choice of only two inputs has remarkable consequences.

“Our model shows that by absorbing only very specific colors of light, photosynthetic organisms may automatically protect themselves against sudden changes — or ‘noise’ — in solar energy, resulting in remarkably efficient power conversion,” said Gabor, an associate professor of physics and astronomy, who led the study appearing today in the journal Science. “Green plants appear green and purple bacteria appear purple because only specific regions of the spectrum from which they absorb are suited for protection against rapidly changing solar energy.”

Gabor first began thinking about photosynthesis research more than a decade ago, when he was a doctoral student at Cornell University. He wondered why plants rejected green light, the most intense solar light. Over the years, he worked with physicists and biologists worldwide to learn more about statistical methods and the quantum biology of photosynthesis.

Richard Cogdell, a renowned botanist at the University of Glasgow in the United Kingdom and a coauthor on the research paper, encouraged Gabor to extend the model to include a wider range of photosynthetic organisms that grow in environments where the incident solar spectrum is very different.

“Excitingly, we were then able to show that the model worked in other photosynthetic organisms besides green plants, and that the model identified a general and fundamental property of photosynthetic light harvesting,” he said. “Our study shows how, by choosing where you absorb solar energy in relation to the incident solar spectrum, you can minimize the noise on the output — information that can be used to enhance the performance of solar cells.”

Coauthor Rienk van Grondelle, an influential experimental physicist at Vrije Universiteit Amsterdam in the Netherlands who works on the primary physical processes of photosynthesis, said the team found the absorption spectra of certain photosynthetic systems select certain spectral excitation regions that cancel the noise and maximize the energy stored.

“This very simple design principle could also be applied in the design of human-made solar cells,” said van Grondelle, who has vast experience with photosynthetic light harvesting.

Gabor explained that plants and other photosynthetic organisms have a wide variety of tactics to prevent damage due to overexposure to the sun, ranging from molecular mechanisms of energy release to physical movement of the leaf to track the sun. Plants have even developed effective protection against UV light, just as in sunscreen.

“In the complex process of photosynthesis, it is clear that protecting the organism from overexposure is the driving factor in successful energy production, and this is the inspiration we used to develop our model,” he said. “Our model incorporates relatively simple physics, yet it is consistent with a vast set of observations in biology. This is remarkably rare. If our model holds up to continued experiments, we may find even more agreement between theory and observations, giving rich insight into the inner workings of nature.”

To construct the model, Gabor and his colleagues applied straightforward physics of networks to the complex details of biology, and were able to make clear, quantitative, and generic statements about highly diverse photosynthetic organisms.

“Our model is the first hypothesis-driven explanation for why plants are green, and we give a roadmap to test the model through more detailed experiments,” Gabor said.

Photosynthesis may be thought of as a kitchen sink, Gabor added, where a faucet flows water in and a drain allows the water to flow out. If the flow into the sink is much bigger than the outward flow, the sink overflows and the water spills all over the floor.

“In photosynthesis, if the flow of solar power into the light harvesting network is significantly larger than the flow out, the photosynthetic network must adapt to reduce the sudden over-flow of energy,” he said. “When the network fails to manage these fluctuations, the organism attempts to expel the extra energy. In doing so, the organism undergoes oxidative stress, which damages cells.”

The researchers were surprised by how general and simple their model is.

“Nature will always surprise you,” Gabor said. “Something that seems so complicated and complex might operate based on a few basic rules. We applied the model to organisms in different photosynthetic niches and continue to reproduce accurate absorption spectra. In biology, there are exceptions to every rule, so much so that finding a rule is usually very difficult. Surprisingly, we seem to have found one of the rules of photosynthetic life.”

Gabor noted that over the last several decades, photosynthesis research has focused mainly on the structure and function of the microscopic components of the photosynthetic process.

“Biologists know well that biological systems are not generally finely tuned given the fact that organisms have little control over their external conditions,” he said. “This contradiction has so far been unaddressed because no model exists that connects microscopic processes with macroscopic properties. Our work represents the first quantitative physical model that tackles this contradiction.”

Next, supported by several recent grants, the researchers will design a novel microscopy technique to test their ideas and advance the technology of photo-biology experiments using quantum optics tools.

“There’s a lot out there to understand about nature, and it only looks more beautiful as we unravel its mysteries,” Gabor said.

Gabor, Cogdell, and van Grondelle were joined in the research by Trevor B. Arp, Jed Kistner-Morris, and Vivek Aji at UCR.

The research was supported by the Air Force Office of Scientific Research Young Investigator Program, the National Science Foundation, and through a U.S. Department of the Navy’s Historically Black Colleges and Universities/Minority Institutions award. Gabor was also supported through a Cottrell Scholar Award and a Canadian Institute for Advanced Research Azrieli Global Scholar Award. Other sources of funding were the NASA MUREP Institutional Research Opportunity program, the U.S. Department of Energy, the Biotechnological and Biological Sciences Research Council, the Royal Netherlands Academy of Arts and Sciences, and the Canadian Institute for Advanced Research.

The research paper is titled, “Quieting a noisy antenna reproduces photosynthetic light harvesting spectra.”

Press release from the University of California, Riverside

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