Transcript Systems biology

Systems biology
-the intro
張晃猷
分子醫學研究所
[email protected]
What is Systems Biology????
To unravel the mysteries of
human biology to identify
strategies for predicting and
preventing diseases such as
cancer, diabetes and AIDS.
http://www.systemsbiology.org/
A cross-disciplinary science
The
The Human Genome Project
Goals
Impact
•
Discovery science vs hypothesis-driven
•
Biology is an Informational Science
•
Tools for high throughput quantitative
measurement of biological information
•
The use of model organisms
Completed
prokaryotes
Archae 19 eubacteria 167
ongoing
Eukaryote 32
eukaryotes
ongoing
Organizational and Descriptional
Levels
So what is Systems Biology?
The definition

The types of biological information (DNA,
RNA, protein, protein interactions, biomolecules,
cells, tissues, etc.) also have their individual
elements (e.g. specific genes or proteins) and the
relationships of these with respect to one
another and the elements of other types of
biological information must be determined, all
of this information integrated to obtain a view
(model) of the system as a whole.
Still vague?

Systems Biology is a new field in
biology that aims at system-level
understanding of biological systems.
Hiroaki Kitano
(Director, ERATO Kitano Symbiotic Systems Project )
What are biological systems?
 Ranges
from ecosystems (eg.
Biosphere) to the system of
reactions that form cellular
biochemistry
A Systems Approach to the Study
of Biological Systems
Some examples
Galactose
utilization/galatosemia

How a defective control
protein (red circle) alters
the level of other
proteins (circles in
shades of gray) through
interactions among
proteins (blue lines) and
interactions between
proteins and DNA
(yellow arrows).
Reverse-engineer the computational
principles underlying cellular processes;
Develop tools and techniques for modeling
and analysis of experimental data at three
levels:
individual genes;
network modules;
whole networks.
Human immunity
m
10 cm
1 cm
100 um
um
nm
CNS
Systems
Networks
Neurons
Synapses
Molecules
1014
connecting
points
Keynote Speakers:
James J. Collins
Center for BioDynamics, Boston University
John Doyle
Control and Dynamical Systems, Caltech
Yoshihide Hayasizaki
Genome Exploration Group, RIKEN Genomic Sciences
Center
Stan Leibler
Laboratory of Living Matter, Rockefeller University
Mark Ptashne
Molecular Biology Program, Sloan-Kettering Institute
System Biology
The quantitative study of biological processes as
integrated systems rather than as isolated parts.
The aim is to understand the interactions between
the myriad of sub-cellular components.
The traditionally separated scientific disciplines,
including physical chemistry, biochemistry,
molecular biology, cell physiology and the
behaviour of multicellular organisms, are unified
by quantitative models.
Advance techniques for global measurements
of subcellular dynamics of gene expression,
proteins, and metabolites will be applied.
The progress will be crucial for a molecular
understanding of many diseases and for
development of novel biotechnological applications.
Expression Experiments
Static: Snapshot of
the activity in the cell
Time series: Multiple
arrays at various temporal
intervals
Time Series Examples:
Development
Development of fruit flies [Arbeitman, Science 02]
Time Series Examples (cont)
Function
Infectious diseases [Huang, Science 01; Nau, PNAS 02]
Interactions
Transcription factors knockout [Zhu, Nature 00;
Pramilla, Genes Dev. 02]
Systems Biology –
from Bioscience to Medicine
Metabolic Flux
 Signal transduction
 Microbial systems
 Methods and softwares
 Spatial models
 Systems biology for medicine

Metabolic flux
From gene expression to metabolic fluxes
Vertical genomics: From gene expression to function ...
and back
Dynamic metabolomics for systems biology
Metabolic networks in motion: High-throughput
analysis of molecular fluxes
Prediction of regulatory pathways using mRNA
expression and protein-protein interaction data:
Application to prediction of galactose regulatory
pathway
Metabolic networks in plants: Statistical analysis and
biological interpretation
Microbial systems biology
Metabolome analysis and cell simulation
Doing it their way: Metabolic differentiation in salmonella
Receptor cooperativity and signal processing in bacterial
chemotaxis
Bacterial persistence: A phenotypic switch revealed by
microfluidics
An approach to generate testable hypothesis in
microbiology
The dynamic response of yeast cells to osmotic shock
Methods and Software for Systems
Biology
Software and methods for modeling and simulating
biochemical networks
A hybrid approach for efficient and robust parameter
estimation in biochemical pathways
A modular approach to building the silicon yeast cell
Model Orchestration: Addressing the challenges of model
management and model composition in systems biology
Dicovering Motifs in Biological Networks using Sub-Graph
Isomorphism
Principles of Systems Biology, illustrated with modeling of
the heart
Spatial Model
Quantitative temporal and spatial analysis of cell division by
4D imaging
Propagating chemical waves within and among cells
Temporal and spatial control of signaling in the interferony/jak/Stat1 pathway
Systems analysis of the quorum sensing phenomenon in a
peculiar plant pathogen Agrobacterium tumefaciens
Compensation effect of MAPK cascade on formation of
phospho-protein gradient
How to make a neurocrystal: Modelling the development
patterning of the fruit fly´s retina
Signal transduction

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Dynamics and design of signalling networks: The Wntpathway
Synaptic signaling: Holding out against noise, diffusion,
and turnover
Employing systems biology to quantify receptor tyrosine
kinase signaling in time and space
Cellular decision making: Control of kinases and
phosphatases on signaling kinetics
Modeling signal transduction systems without ignoring
their combinatorial complexity
New quantitative approaches for modeling and
simulation of large signal transduction networks reveal
novel insights into programmed cell death
Systems Biology and Medicine

Mathematical Modelling of metabolic diseases

Virus dynamics: Modeling of influenza A virus replication

Discovering activated regulatory networks in the DNA
damage response pathway of yeast

Metabolic comparison of the in-silico phenotypegenotype relationship of Pseudomonas putida and
Peudomonas aeruginosa

Systems biology approach to understand the stress
response of P. aeruginosa to host innate immunity

Using a mammalian cell cycle simulation in anti-tumor
pharmaceutical development to interpret differential
kinase inhibition and biological knock-outs
The position of Systems Biology
What does it take to carry out
Systems Biology?

A cross-disciplinary faculty who speak and understand
the languages of different disciplines

Integrate new global technologies with the data
acquisition, storage, integration, and analysis tools of
computational biology and mathematics.

High-throughput facilities for genomics, proteomics etc…

An integration of effort with academia and industry.

Integration of discovery science with hypothesis-driven
science for the integrated global analysis of systems.
In another word……
Why do we care about biological
systems?


Ability to figure out what the effect will be of
an intervention in one part of the system
What intervention one has to make in order
to obtain some desired result
= Which protein should be either activated or
deactivated in order to stop a particular
disease process while doing the least harm
to the patient?
Where do computers
come in?


Systems modeling
simulation, reasoning, discovery
Some properties to investigate
Structure
Dynamics
Robustness
Methods of control systems
Methods to design and modify for desired
properties
The SYSTEOME Project

Systeome is an assembly of system profiles for
all genetic variations and environmental stimuli
responses.

Goal: to complete a detailed and
comprehensive simulation model of the human
cell at an estimated error margin of 20% by year
2020, and to finish identifying the system profile
for all genetic variations, drug responses, and
environmental stimuli by 2030.

Dr. Hiroaki Kitano
Conclusion

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
System biology is a new and emerging field in
biology
A long ways to go before understanding
biological systems
“… systems biology will be the dominant
paradigm in biology, and many medical
applications as well as scientific discoveries are
expected” – Hiroaki Kitano
Further readings
Biological System Sample
Biological System Sample
Gene Expression and Regulation
Intra- and Inter-Cellular
Dynamics
Heat-Shock Regulation
Biology in a Nutshell
(for people with little knowledge but infinite intelligence)
 Genome
(ROM): assembly
code on how to build proteins
Genomes
3
Gene
Products
C, T, G
variables  amino acid
Structure
& Function
 Genome consists of genes
 Protein: Object
description Object instantiation
 Gene
 Protein
 Instructions: A,
Functions
 Enzymes:
proteins that catalyze
biochemical reactions
Pathway: sequence
 Network
of reactions
(directed graph): set of
pathways with metabolites as vertices and
enzymes as edges
Pathways &
Physiology