Biological systems are complex networks of biologically relevant entities that operate at different scales, ranging from the macro (population level) to the micro-to-nanoscopic (cell, organelle and tissue levels). These networks exhibit properties such as biocomplexity and diversity, which allow organisms to adapt to changes in their environment.

The complexity of biological systems has been recognized since the first half of the 20th century, and methods to understand parts and their interaction at the molecular level have been developed. These studies have been crucial to advancing our understanding of how cells, tissues and entire organisms function, and how they can be designed to perform specific tasks.

Many of the most important features that underlie the behaviour of biological systems emerge from the interactions of many molecular components, all acting together. These collective properties are called “emergent properties” and are often critical to understanding how a system works.

This field of research is rooted in biology, but also includes engineers and scientists who are applying their knowledge to the design of new synthetic systems. This integration of biological and engineering perspectives is the foundation for what is known as “synthetic biology.”

EESA’s Environmental & Biological Systems Science Program Domain focuses on expanding our understanding to predict how living systems are organized and function, from molecular to watershed and reservoir levels. This is a critical task, as it helps us to understand how ecosystems and the Earth’s energy reservoirs operate, and ultimately how these natural processes can be harnessed for human benefit.

For example, researchers are working to understand how a plant sequesters carbon dioxide and stores it in cellulose and other polymers that make up the plant body. This work is enabling scientists to create yeasts that can be used to make ethanol, which could one day replace gasoline as a source of fuel.

A key part of this work is developing computer models that simulate real complex systems. These models capture the essence of the complexity, abstracting it into a manageable size that is cognitively, mathematically and theoretically explainable. Models are also used to predict how a system will respond to various stimuli, and to test hypotheses about how to modify or fix the system.

Synthetic circuits have also been engineered in the context of multicellular systems to better understand how cells behave when stimulated by different types of signals, such as freely diffusing molecules like acetone-hydroxyl radical (AHL). These synthetic systems are comprised of well-characterized natural modules that represent two types of cell types within a bacterial population.

It is important to note that while synthetic circuits have been developed, they are still at a very early stage of development. This is because it is challenging to build synthetic circuits that can be tested to see whether they are effective in a variety of situations and conditions.

Moreover, the ability to build synthetic circuits will be limited until we have the technological capabilities to synthesize entire genomes from scratch, and thus to make multiple gene additions and modifications. This will increase the complexity and potential of synthetic circuits to become functionally specific.