Systems and Synthetic Biology

Book Preface

Abstract In the mid 1990s when Leroy Hood reintroduced the term “Systems Biology”, the fusion of ideas gave rise to confusion to such an extent that there used to be special talks on ‘what is systems biology’? Over the last decade, Systems Biology has undergone directed evolution leading to the emergence of personalized versions of this term. Irrespective of this, strong computational dependency and a significant increase in the scale of investigation often appear as constant features in the systems biology background. In our opinion, Systems Biology is an approach that involves the following (a) experimental and computational studies describing collective behavior of molecules in relation to the pathway and networks, and with the higher-level physiological outcome (b) new experimental and mathematical methods important to study group behavior of interacting components. This chapter describes the origin and evolution of systems biology, as a formal discipline, steps and challenges in building models and their potential applications.

The traditional approach of doing science has mainly centered around the twin strategy of observation and classification i.e., observe some measurable quantity, say flower color, height of plant and so on, collect data from a large number of plants and try to find some non-obvious pattern. At least in biology, the role of analytical techniques has rarely been pursued as a serious scientific discipline. This is due to the fact that in the traditional setting biological data was easily countable and available to human analysis and interpretation. The science of taxonomy was built upon the foundation of finding common patterns among a large number of samples and categorizing them hierarchically. The strategy was that a higher-level abstraction should be shared by all the members of the group, which can be further sub-sorted into various bins based on some additional parameter. Thus, you see kingdom, families, genus and species as a top-down flow of information in taxonomy. Charles Darwin stretched the idea of ‘finding patterns from external observations’ further, and ended up his long and careful study by proposing the theory of Natural selection. Lamarck and other scientists extended the story further and tried to make his story predictive.

However, in all these situations classifying organisms did not explain how they worked. There was a need to adopt a different approach. Mendel made the first bold attempts to look beyond a horizontal (population-based) plane of vision and vertically move down from phenotype to causal elements. He assumed a linear correlation between a causal element and a phenotypic observation. It was a groundbreaking work. In absence of any high-resolution physical device, he could generate accurate rules and predictions of inheritance simply by looking at the external phenotypes.

After Mendelian era, the science of biology got predominately biochemical and microscopic. Technological developments helped scientists move from external phenotype to cell interiors. However, due to technical complexity and cost of data generation, biological data was mostly qualitative, studied at the level of human analysis and did not require special mathematical techniques and computational infrastructure for interpretation.

As the technological tools got more sophisticated, scientists moved from external observations to the study of cells, chromosomes, DNA, protein and so on. Having seen so many parts co-existing in a small cellular space, there was a natural curiosity—how are these parts created, used, retired, recycled. What is the role of these parts in determining higher order behavior?

Two parallel efforts were aggressively pursued: (i) uncover as many parts and modules (collection of parts employed for a single purpose) as possible, and (ii) find the role of each part in determining a given phenotype.We call this strategy as ‘reductionist biology’i.e., reduce a system to a set of components and study each component separately. The Human Genome Sequencing Project was started precisely keeping the first aim of reductionist biology in mind i.e., if we know our genetic blueprint, we will figure out everything about ourselves. In parallel to this, a large body of mutations and chromosomal aberrations was collected from diseased tissue to correlate abnormal physiological/morphological conditions with the underlying genetic cause.