Systems Biology
Systems biology is the study of biology through systematic perturbation, the global read-out of the multifaceted response and integration of these data to formulate predictive models1. Classical biology is based on a reductionist model in which the systems are first broken down into their single components, and subsequently, the various “pieces” are reintegrated into the system. This approach, however, because of the enormous complexity of biological processes, has many gaps due to the inability of scientists to intellectually master the process of the mechanisms’ integration.
In contrast “systems biology”, by looking at the cellular macrocosm and employing a large-scale perturbation at genetic and environmental levels, is able to simultaneously monitor the entire process, indeed acting, at genic, proteic, metabolic and phenotype levels.The formation of a model happens through a multi-step process: first the reference model is selected (it can be a cell line, a tissue, a single organism or a population of individual organisms), then it moves to induction of a perturbation that can be genetic (silencing or activation of key genes), protein expression (transfection to over-express or down-regulate the expression of one or more protein), or environmental (with exposure to chemicals or alteration of the natural habitat of the organism).
Once the model is validated and its homeostasis disrupted, we reach the real aim of the study, which proceeds via advanced biotechnology techniques that comprise genomic studies, proteomics, transcriptomics, bioinformatics and mathematical- statistics.
Systems biology essentially depends on the ability of the scientist to develop a reliable model. Scientists in this field require the ability to span many layers of abstraction in detail, employing statistical mining, alignment across data sets, probabilistic inference, differential equations and data visualization. All the above will enable him to formulate a predictive model compared to that system.
The “goal” of systems biology, therefore, is to form a modeling in which, thanks to data collected through study and observation of the many facets of the system, we can understand how the cell or organism is self-organized in response to a given perturbation and, how the same process can evolve differently in the case of a different perturbation. Consequently, the scientist has to verify if and how the system reacts autonomously, seeking to restore initial homeostasis or otherwise, a balance that will still allow the continuation of this life, or lead it to the interruption of the same.
The importance of this new approach is in opposition with the approach invested in the past decades in biotechnology. Often reasons of “business” have set individual cellular processes in charge of entire theories on the overall functioning of biological processes.
Prof. Giovan Giacomo Giordano anticipated systems biology in his teachings. He often invited his students to “understand not only what is built, but also how the various parts can be combined, how they are combined and how they work as an integrated complex.”
In summary, this new discipline proposes not only to understand how systems are organized and with which instruments they can self-organize, but also to provide new tools for diagnostics through the identification of genetic risk factors for diseases, and to achieve model-based personalized treatment regimens which will possibly eliminate all the benefits and risks.
This approach provides, in the end, possibilities that suggest the opening of new avenues for drug discovery.
Bibliography
[1] Ideker et al, A new approach to decoding life: systems biology.
Annu. Rev. Genomics Hum. Genet 2, 343 (2001)
[2] Priami, Informatica e biologia dei sistemi
Mondo digitale, Num.1 (2004)
[3] Ideker I., Bandyopadhyay S. , Integrative systems biology
Nature Genetics, Nature Publishing Group (2010)
Davide Mangani Rizzo