An introduction to SYSTEMS BIOLOGY Paolo Tieri CNR Consiglio Nazionale delle Ricerche, Rome, Italy 10 February 2015 Universidade Federal de Minas Gerais, Belo Horizonte, Brasil
Course outline Day 1: intro on systems biology and network biology D2: overvew of tools and resources for network biology D3: simple case study with Cytoscape and other resources D4: some successful network approach cases from literature
Seminar outline What is Systems Biology Introduction to Network Biology
CNR http://www.iac.cnr.it/ its duty is to carry out, promote, spread, transfer and improve research activities in the main sectors of knowledge growth and of its applications for the scientific, technological, economic and social development of the Country Largest interdisciplinary research body in Italy 7 broad Departments 100 Institutes 8000 workers
What is Systems Biology Systems biology is the study of *how molecules interact and join together to *give rise to subcellular structures and machinery that *form the functional units *capable of operations that are needed for cell, tissue/organ level physiological functions
Systems Biology Recent field: biology-based interdisciplinary study field that focuses on complex interactions in biological systems Rapidly making progress (proliferation of dedicated institutes, teams, works, literature) Aims to system-level comprehension Possible only today, thanks to knowledge advancements, high throughput technologies, affordable computing power
The basis of SB Rooted in enzyme kinetics modeling (1900-1970) Explosion from studies of genome (1990) It also fostered advancements in molecular biology and relative technologies Needs a deep understanding of organisms at molecular level as a basis for understanding at system level Ambition of systems biology is the modeling and discovery of emergent properties
Why systems matter A system is a group of parts that come together, interacting and interdependent, to form a more complex whole The whole is greater than the sum of the parts
Alphabet, words, sentences, books, literature Take six letters: E, I, L, N, S, T LISTEN, or SILENT Evangelist à Evil's Agent!!! words are objects that emerge from the composition, position and interactions of letters, following given grammatical protocols
Up to the next level words The of a compose not is the single in that sense it sentence The sense of a sentence is not in the single words that compose it Sentences emerge from words composed following specific syntax rules, and are the result of interacting words
In summary Individual parts from simpler/lower level can combine in unexpected ways into a "system The interaction of the parts in this system creates important *properties or functions we would *not expect from looking at the individual parts, each on their own
Emergent properties We call these properties and functions that arise from the interacting parts in a system "emergent properties : they are central to the study of systems Emergent entities (properties or substances) arise out of more fundamental entities and yet are novel or irreducible with respect to them
Complex systems Emergence is typical in complex systems A system is complex if its emergent properties are not easily predictable à no linear output The output of a nonlinear system is not directly proportional to the input (that is another way to say that the whole is not simply the sum of the parts )
Complex systems Four basis ACGT humankind s genetic makeup (approximately 19000 genes, latest estimation) 20 amino acids ~50000 proteins produced from these genes à the extraordinary functions of human beings (emergent properties), and the corresponding complexity of a human being as a system
From molecule to system system level : molecular biology focuses on biomolecules, systems biology focuses on the whole ensemble of molecular components, scaling up to the whole organism a system is composed by its components, but its essence its being a system - intimately relies on the connection and the dynamics of its components It is not possible to fully describe a system simply listing its components without describing their relationships
Global view (parts+system) At the same time one cannot neglect the nature of components, since their global dynamics depends also on their intrinsic characteristics To know the structure alone of a system without knowing the features of its parts is little informative Both structure of the system and components play an indispensable role forming symbiotic state of the system as a whole (Kitano)
Holism vs Reductionism Systems biology is holistic à the parts of something are intimately interconnected and explicable only by reference to the whole, in contrast to classical biology that has been (and is) reductionist à analysing and describing a complex phenomenon in terms of its simple or fundamental constituents
Not a war! Reductionism has been fundamental to understand the nature of biological constituents But today we have the chance to move on and try to reconstruct the single parts into the whole
SB is an integrated approach that aims to... 1) Comprehension of the structure of the system, both real and virtual (neuronal networks, physical bounds; metabolic & signalling networks, genetic regulation networks)
2) Comprehension of the dynamics of the system, by means of qualitative and quantitative analysis (kinetics), and relative modeling
3) Comprehension of system control and regulation procedures: the principles that drive the dynamics
4) Finally, comprehension of the original design of the system, principles of self-organization (the instruction manual that you need to put the parts together)
In summary We need to reconstruct together: Components Structure Dynamics Controls Architecture
http://youtu.be/hcfozdlv4fy
SB is a broad discipline Given these premises, systems biology is a broad concept that can be considered under diverse aspects
SB is a field of study In the most common meaning, SB is the field that studies the complex interactions among biological systems components
SB is a paradigm Paradigm antithetic to reductionism (i.e.: reduce a complex object to its constituents and analyse them) Reductionism can be overtaken/supported by SB s holistic approach SB deals with reassembling instead of disassembling, reconstructing instead of dismantling, integrating instead of reducing, observe the whole instead of the single parts
Multiscale integration: Physical & temporal Hunter & Borg, Integration from proteins to organs: the Physiome Project, Nat. Rev. Mol. Cell. Biol. 2003
Operating research protocol, i.e. recursive sequence of steps that includes: SB is a protocol A) established knowledge & theory B) hypothesis generation & computational modeling C) experimental validation D) acquiring quantitative description A ) enhanced/new knowledge & tuning up of the theory B ) improved hypothesis & computational model C )
SB is a scientific phenomenon socio-scientific phenomenon that regards the strategy devoted to pursue the integration of massive, heterogeneous data coming from different experimental sources, different methodologies & instrumentation, and people from disparate scientific background
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SB techniques & approaches trascriptomics: gene expression (microarrays) proteomics: protein & expression profiling (i.e. mass spectrometry) metabolomics: metabolite identification & measurement in a cell or tissue Interactomics / network biology: identification of dynamics & topology of interaction among proteins, genes, cells functional genomics: genes function & interaction
Focus on integration... Different data (multi-omic) Different techniques Different methodologies Data from different sources Different competencies: biology, medicine, maths, physics, informatics, statistics, engineering
and modeling Development of mechanistic models reconstruction of dynamic systems from the quantitative properties of their elementary building blocks e.g., cellular networks and pathway cascades are often reconstructed, modeled and simulated to infer predictions DE models, agent-based simulators
Computing & mathematics are essential tools for: System kinetics, dynamics Integrative modeling Handling high dimension data (multifactorial dependencies, statistical approaches) Simulation (computing power)
Usually, systems complexity is inversely proportional to models complexity
Universal principles Efficacy of the SB approach also relies in the study of universal organizing principles, architecture and large-scale organization of living matter (but not limited to the biological fields, since these principles often apply to the technological/ social fields too, among others)
Life s complexity pyramid Integration of different data layers, at structural and regulatory level The comprehension of cell organizational logic is obtained by means of the observation of the cell as a complex network of functionally linked components
Modules nested in a hierarchical architecture In turn they represent the bio-bricks of functional modules (functionally distinct & autonomous sets) Genes, RNA, proteins and metabolites selforganize into regulatory motifs and metabolic pathways Genome, transcriptome, proteome and metabolome Oltvai & Barabasi, Life s complexity pyramid, Science 2002
Nevertheless individual components are specific for each single organism, topological properties of cellular networks share many similarities with networks of different nature, such as social, technological or ecological networks This evidence suggests the existence of organizing principles that applies to every kind of network, from the cell to the Internet
Complex systems: key concepts in pictures http://youtu.be/dkd3l6i-olw From http://www.fotonlabs.com And https://www.udemy.com/complexitymanagement/
Source: D. Noble; Wolframalpha