an introduction to systems biology - cnr

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 •  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

Hunter & Borg, Integration from proteins to organs: the Physiome Project, Nat.

Rev. Mol. Cell. Biol. 2003

Multiscale integration: Physical & temporal

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

file://localhost/.file/id=6571367.54435276

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…

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

Oltvai & Barabasi, Life’s complexity pyramid, Science 2002

Genome, transcriptome, proteome and metabolome

Genes, RNA, proteins and metabolites self-organize into regulatory motifs and metabolic pathways

In turn they represent the “bio-bricks” of functional modules (functionally distinct & autonomous sets)

Modules nested in a hierarchical architecture

•  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/complexity-management/

Source: D. Noble; Wolframalpha