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 inter- disciplinary 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 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
SB is a protocol Operating research protocol , i.e. recursive sequence of steps that includes: • 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 (multi- factorial dependencies, statistical approaches) • Simulation (computing power)
Usually, systems complexity is inversely proportional to models complexity …
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