Systems Biology in Nanosafety Research

Abstract

In his famous essay, Lazebnik [1] discussed whether a biologist can fix a broken radio and suggested that applying the ‘biologist approach’ to a broken radio will likely not lead to a successful end, while any engineer or even a trained repairman evidently could fix the radio. In biology, the study of molecules one by one is fine for gathering information on how molecules work, but deciphering biological mechanisms, or the function of biological systems, is a different story. One difference between an engineer and a biologist, according to Lazebnik, lies in the language: in biology, language is oftentimes vague and nonquantitative which limits the possibility of making predictions [1]. In systems biology, a quantitative and predictive language is adopted to describe biological knowledge in order to understand how molecules act together within the network of interactions that makes up a living system. Systems biology, in other words, is the holistic analysis of complex systems. Indeed, systems biology can be defined as the computational and mathematical modeling of complex biological systems, in contrast to the traditional, reductionist approach to biology. Common technology platforms that are deployed to obtain complex datasets are transcriptomics, proteomics, metabolomics and epigenomics. However, systems biology should not be seen merely as the generation of lists of genes, proteins or metabolites using such omics platforms; the objective is to exploit these data and to develop quantitative models that describe the biological system and its response to individual perturbations (see [2] for an excellent introduction to this subject). Furthermore, systems biology can be seen as an iterative interplay between discoveryand hypothesis-driven science: “global observations (discoveries) are matched against model predictions (hypotheses) in an iterative manner, leading to the formation of new models, new predictions, and new experiments to test them” [2]. Systems toxicology, in turn, has been described as “the integration of classical toxicology with quantitative analysis of large networks of molecular and functional changes occurring across multiple levels of biological organization”, and it has been suggested that its application could be part of a new and improved risk assessment [3]. This is nothing less than a paradigm shift in the way that toxicology is conducted. Importantly, systems toxicology – and systems biology in general – relies heavily on computational approaches to manage, analyze and interpret the data generated by large-scale experiments, and computer databases are thus an integral feature of this approach [2]. To this end, commonly accepted repositories and software environments are crucially important [4]. This does not mean that the introduction of systems toxicology approaches is breaking the rice bowl of the classically trained toxicologist. Instead, the ‘new’ toxicology is Systems biology in nanosafety research