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What is Systems Biology?
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ICBS 2008
- More than 1000 participants!!
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Outline
1. What is Systems Biology?2. Why a need for Systems Biology (motivation)?3. Biological data suitable for conducting Systems Biology 4. Using a mathematical model in biological research.
5. Examples of systems; signal transduction pathwaysmetabolic pathways etc
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What is Systems biology?
Central Dogma
• The central dogma of information flow in biology: Information flows from DNA toRNA to protein. With other words: the amino acid sequence making up a protein, itsstructure and function, is determined by the DNA transcription.
• “This states that once ‘information’ has passed into protein it cannot get outagain. In more detail, the transfer of information from nucleic acid to nucleic acid,or from nucleic acid to protein may be possible, but transfer from protein toprotein, or from protein to nucleic acid is impossible. Information means here theprecise determination of sequence, either of bases in the nucleic acid or of aminoacid residues in the protein.”Francis Crick, On Protein Synthesis, in Symp. Soc. Exp. Biol. XII, 138-167 (1958)
DNA RNA PROTEINTRANSCRIPTION TRANSLATION
REPLICATION
www.brc.dcs.gla.ac.uk, David Gilbert, Systems Biology (1) Introduction
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What is Systems Biology?It is an approach where scientists investigate biology at a system level!!
What does this mean?
Have we not always done that?
Well, to some extent!
Theoretical biologist have done that for a long time, butwith little supporting experimental data.
Up to now we have prepared a cellular map of proteins involved in different pathways and biological processes. This is a rather static map. What we do not know to a large extent is the dynamics of these pathways and how different processes are linked and dependent on each other in a timeand space-dependent manner. We need to move from qualitative descriptions to more quantitative descriptions.
Integrative Biology!
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What is Systems Biology?An approach to study biological systems in an integrative way
1. Often biologists who use large-scale data (global view) in order to cluster genes / proteins involved in the same functional group. Proteins with unknown function can be functionally linked to a biological process. These biologists orbioinfomaticians look at biological systems with a more holistic view.
Science 14 December 2001:Vol. 294. no. 5550, pp. 2364 - 2368
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What is Systems Biology?
2. Biologist who focuses on particular biological systems and tries to understand systemproperties such as feedback loops, amplification, cross-talk etc. They could also integrate biological events at different levels. This often requires quantitative analysis of biological processes at different levels.
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DHAP
G3P
GlycerolTranslation
Gpd1, Gpp2,….
Gpd1
Gpp2
Signalpathway
Metabolism
Fps1
Osmotic stress
Osmoticstress
Glycerolextern
Plasma membrane
cytosol nucleus
Πe
Πi
MAP kinase cascade
Phospho relaysystem
Hog1
TranscriptionGPD1, GPP2,….
Gene expressionSsk2 Ssk2P
Pi
Pbs2 Pbs2P Pbs2P2
Pi
ATP ADP ATP ADP
Pi
Hog1
Ssk1
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v2MAP
v-1MAP
v3MAP
v-2MAP v-3
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Pi
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Pi
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MAP
v-4MAP v-5
MAP
⊕
⊕
⊕
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mRNAnuc mRNAcyt
Proteinsnucleus
cytosol
vts
vex vrd
vpdHog1nuc
Hog1
vtrans
vtrans1
vtrans2
Glucose
Gluc-6-P
Fruc-1,6-BP
GAP DHAP
Pyruvate
Ethanol
synthesis
synthesis
3 CO2
G3P
Glycerol
NADH NAD
ADP ATP
4 NAD
4 NADH
NAD
NADH
NADH
NAD
2 ADP2 ATP NADH NAD
ATP
ADP
ATP
ADP
ATP ADP
ADP ATP
Glk1
Gpp2Gpd1
Fps1
Glucose uptake
Glycerol, ex
Phosphorelay module
MAP kinasecascade module
Gene expression module
Biophysical changes
Πi = f(Glycerol)Waterflow over membrane = f(Πi, Πe, Πt)Volume change = f(Waterflow)
(see text)
Internal osmotic pressure
External osmotic pressure
Metabolismmodule
vdephos
Ptp2vtl
v15
v14
v16
v13
v12v11
v3
v10
v1
v2
v4
v5
v6
v9
v7 v8
Edda Klipp et al, Nature Biotechnology 2005, number 8,
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3. Theoretical biologist or computational biologist who studies biological systems using and/or develop computational tools. Often they develop mathematical models of biological systems.
What is Systems Biology?
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Goal 1: To define e.g. proteins networks. Often genome-wide data are used. To group proteins ofunknown function to functional groups. Filling gaps of knowledge!
Goal 2: Is to understand complex systems by combining mathematical modelingand experimental studies. Systems biology offers the chance to predict the outcome of complexprocesses. How do cells work ? How are cellular processes regulated? How do cells react toenvironmental pertubations? Etc etc etc etc etc
Goal 3: To understand dynamic properties of biological systems by pure experimental techniques.
Mathematical modelers Experimentalists
Systems Biologists
http://pubs.acs.org/cen/coverstory/8120/8120biology.html
What is a Systems Biologist and who is one?
This might be the most commonly
described systems biologist
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What is Systems Biology?
The information about how a system works demands studies of how proteins work together in the context of the organ / tissue / cell etc.
http://www.zum.de/Faecher/Materialien/beck/bilder/transsri5.jpg http://www.biochem.northwestern.edu/mayo/Lab%20GIF%20Images/Signaling.gifocw.mit.edu/.../0/chp_subtilisinbp.jpg
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What is a biological system?:
1. Consists of components that interact such in order to form a functional unit.
2. Defined at different hierarchical levels with different extent of detail (enzyme, glycolysis, cellular, tissue, organ, whole organism, ecosystems).
System biology, Definitions and perspectives, Topics in current Genetics 2005
What is Systems Biology?
www4.liber.se/kemionline/gymkeb/bilder/12_a.jpg http://biologi.uio.no/plfys/haa/gif/form142.gif http://www.acuhealthzone.com/images/anatomy_of_human_body.gif
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What is Systems Biology?Quantitative versus Qualitative??
Qualitative analysis: It tries to answer the questions why and how, it catagorises datainto patterns. In biology, qualitative research has provided a huge amount of informationwhich is the basis for today´s and future research. It has been the basis for the reductionist era of molecular biology.
Quantitative analysis: It tries to answer the questions what, where and when, relies onthe analysis on numerical data which can be quantified, time-series data. In SystemsBiology, the temporal and spatial dynamics of each molecular spicies are of interest!
(ref: http://en.wikipedia.org)
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What is Systems Biology?
Pieces into systems..
1. Understanding how biomolecules (proteins, metabolites, RNA....) function together (i.e. in a system), rather than in isolation. System-level understanding!
2. In order to explain function, therefore, systems biology argues that we should take a more holistic view of biological phenomena, one in which function emerges at a higher-than-molecular level. This is the level of ‘systems’, whose behaviour is described by topological, not physico-chemical, laws. (Hiroaki Kitano)
2. Airplane analogy (Hiroaki Kitano)
3. To get a system-level understanding you need to know: the system structure(protein-protein interactions, biochemical pathways etc), System dynamics (how does a system behave over time?) Few systems with this understanding!
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Why a need for Systems Biology (motivation)?
Nucleotide sequence Nucleotide structure
Gene expression
Protein sequence Protein function
Protein-protein interactions (pathways)
Cell
Cell to cell signalling
Tissues
Organs
Physiology Organism
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Why a need for Systems Biology (motivation)?
1. Genome-wide data sets (transcriptomics, proteomics, mass-spec based analysis etc) provide the opportunity to start integrative research.
2. Genome-wide data sets allow identification of large-protein networks thus filling gaps of knowledge.
3. From a biological point of view thi s is a natural step to take as we have a ratherlarge base of knowledge of many pathways.
Mathematical modeling:
3. Testing if the biological hypothesis is accurate – is it likely that the experimental data explains the model?
4. Testing quantitative predictions of behaviors. This allows us to minimize the number of experiments and do the critical ones which can give us most information. – Experimental planning!!
5. A model provides the opportunity to address critical scientific questions.
6. Cellular regulation depends on time and space, which a model can address.
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Sln1AspP
ATPADP
Ypd1
Ssk1AspP
Pi
high osmolarity?
Ypd1HisP
Ssk1
Sln1HisP Sln1v1
TCSv2TCS
v3TCS
v4TCS
v5TCS
Sln1
Ssk1
Hog1Glucose
DHAP
G3P
GlycerolTranslation
Gpd1, Gpp2,….
Gpd1
Gpp2
Signalpathway
Metabolism
Fps1
Osmotic stress
Osmoticstress
Glycerolextern
Plasma membrane
cytosol nucleus
Πe
Πi
MAP kinase cascade
Phospho relaysystem
Hog1
TranscriptionGPD1, GPP2,….
Gene expressionSsk2 Ssk2P
Pi
Pbs2 Pbs2P Pbs2P2
Pi
ATP ADP ATP ADP
Pi
Hog1
Ssk1
v1MAP
v2MAP
v-1MAP
v3MAP
v-2MAP v-3
MAP
ATP ADPATP ADP
Hog1P Hog1P2
Pi
ATP ADP ATP ADP
Pi
v4MAP v5
MAP
v-4MAP v-5
MAP
⊕
⊕
⊕
Hog1P2
Hog1P2nuc
mRNAnuc mRNAcyt
Proteinsnucleus
cytosol
vts
vex vrd
vpdHog1nuc
Hog1
vtrans
vtrans1
vtrans2
Glucose
Gluc-6-P
Fruc-1,6-BP
GAP DHAP
Pyruvate
Ethanol
synthesis
synthesis
3 CO2
G3P
Glycerol
NADH NAD
ADP ATP
4 NAD
4 NADH
NAD
NADH
NADH
NAD
2 ADP2 ATP NADH NAD
ATP
ADP
ATP
ADP
ATP ADP
ADP ATP
Glk1
Gpp2Gpd1
Fps1
Glucose uptake
Glycerol, ex
Phosphorelay module
MAP kinasecascade module
Gene expression module
Biophysical changes
Πi = f(Glycerol)Waterflow over membrane = f(Πi, Πe, Πt)Volume change = f(Waterflow)
(see text)
Internal osmotic pressure
External osmotic pressure
Metabolismmodule
vdephos
Ptp2vtl
v15
v14
v16
v13
v12v11
v3
v10
v1
v2
v4
v5
v6
v9
v7 v8
Example of a model which links together different biological processes taking into account time and space, e.g. the compartments cytosol and nucleus are included.
Why a need for Systems Biology (motivation)?
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Why a need for Systems Biology (motivation)?
5. If you have a model you can analyse which parts of the system which contributemost to the desired properties of the model.
6. Signaling networks can interact in multivarious ways which complexity requires a model.
7. Investigate the principles underlying biological robustness. It is an essential property of biological systems (Kitano H, Science v.292, 2002). ”The persistent of a system´s characteristic behaviour under perturbation or conditions of uncertainty” (System modeling in cellular biology, zoltan Szallasi et al, 2006).
What design elements are thought to be required to avoid harmful disturbances: 1) redundancy (back- up systems) 2) Feedback control 3) Structure complex systems into modules which have semi-autonomous functions etc etc.
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THE EQUILIBRIA OF LIFE
NUTRIENTS
TEMPERATURE
CHEMICALS
WATER AVAILABILITY
COMPETITION WASTE
RADIATION SURVIVAL
OPTIMISATION OF GROWTH
From Marcus Krantz
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Why a need for Systems Biology (motivation)?
8. To understand general ”design principles” shaped by evolution; some peoplebelieve that there exist functional modules as a critical level of biological organisation (ref. Hartwell L.H. Nature 1999, vol 402, 2 Dec). A module ” a discrete entity whosefunction is separable from those of other modules”, e.g. a ribosome whichsynthesizes proteins is spatially isolating its function, signalling pathways etc.
What are ”design principles” : e.g. positive or negative feedback-loops, amplifiers, parallel circuits (common terms to engineers)? Are they found in nature?
Negative feedback: reduces outputPositive feedback: increases output, or Bipolar feedback: Either increase or decrease output.
What is important for mathematical modeling is Quantitative experimental data!!!!
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Hypothetical module
A signalling pathway provides the means for the cell to sense aspects of its surroundings and/or condition. It usually consists of:
A sensor or receptor able to respond to theenvironment.
One or more cytoplasmic signal transducers, perhaps acting on cytoplasmic targets.
A shuttling component able to carry the signal into the nucleus, activating
one or more transcription factors.
Mechanism of feedback control.
Kinases and phosphates are common, using (de)phosphorylation as the signal.
PLASMA MEMBRANE
CY
TOSO
LN
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S
GENE EXPRESSION
NUCLEAR MEMBRANE
From Marcus Krantz
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Biological data suitable for conducting Systems Biology
Experimental techniques steadily improves in the direction of Systems Biology
- Large Scale studies (-Omics) which produces an enormous amount of data at different levels of cellular organization. This data can be integrated into mathematicalmodels and / or analysed computationally to fill gaps of unknown players. These methods constantely improves and new arise.
- Improved conventional methods; better quantification methods, single-cellanalysis methods (e.g. microscopy with microfluidic systems), quantitative measurements of gene expression, protein levels etc.
-Increased awareness of studying the favourite system quantitatively instead of qualitatively leading to improved techniques and an increased usage of certain methods. This awareness might lead to better planned experiments if using a mathematical model. Experimental planning!
-To include engineers in biology will lead to improved or new highly sophisticatedtechniques. And more statistical analysis!!!
According to the interpretation of System Biology as the ability to obtain, integrate and analyze complex data from multiple experimental sources using interdisciplinary tools
http://en.wikipedia.org/wiki/Systems_biology#Techniques_associated_with_systems_biology
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Omics -
Focuses on large scale and holistic data/information to understand life in encapsulated omes
- Genomics (the study of genes, regulatory and non-coding sequences )
- Transcriptomics (RNA and gene expression)
- Proteomics (Systematic study of protein expression)
- Interactomics (studying the interactome, which is the interaction among proteins)
-Metabolomics (the study of small-molecule metabolite profiles in cells)
- Phenomics (describes the state of an organism as it changes with time)
- and so on......
Biological data suitable for conducting Systems Biology
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Using a mathematical model in biological research.A mathematical model: By using mathematical language you can describe a system;can be found in many disciplines such as in engineering, economics and meteorology.
It is a descriptive model of a system as a hypothesis of how the system could work
It consists of a set of variables and a set of equations that establish relationshipsbetween the variables.
http://en.wikipedia.org/wiki/Numerical_weather_prediction
An example of 500 mbar geopotential height prediction from a numerical weather prediction model
Examples of Economic models
Black-Scholes option pricing modelHeckscher-Ohlin model
International FuturesIS/LM model
Keynesian cross model
http://en.wikipedia.org/wiki/Economic_model#Examples_of_economic_models
Example of a Meteorological model
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• Start with a problem of interest
• Make reasonable simplifying assumptions
• Translate the problem from words to mathematically/physically realistic statements.
• Use experimentally derived data; one training data set and one set of verification data. The training data set should be used to estimate model parameters and the verification data set should be used to test the system. The better fit: the better model.
• Simulation: Imitation of real biology scenarios.
• Predictions: Statements or claim that a particular event will occur
Different steps in the modeling procedure:
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Limitations:1. Not necessarily a ‘correct’ model2. Unrealistic models may fit data very well leading to incorrect conclusions3. Simple models are easy to manage, but complexity is often required4. Realistic simulations require a large number of hard to obtain parameters5. Models are not explanations and can never alone provide a complete
solution to a biological problem.
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Examples of systems
Yeast. 2007 Nov;24(11):943-59
MAPK-signalling pathway Metabolism
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Examples of systems
I. Swameye, PNAS, Feb.4, 2003
Core model
JAK-STAT signaling pathway
-Hormone (Epo)
-Receptor binding Epo
-Binding leads to transphosphorylationof JAK2 and phosphorylation of the cytoplasmic receptor domains.
-Phosphotyrosine residues 343 and 401recruit monomeric STAT-5 (x1), which gets phosphorylated (x2), it then dimerises (x3),and migrates to the nucleus (x4).
In nucleus: Stimulated transcription of targetgenes.
What happens then?
Biology
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Examples of systemsData - Simulations
A + B : experimental data
C + D : testing two hypothesisTime-series measurements
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How is Systems Biology conducted? How did we do?
A signalling pathwayIn yeast – HOG pathway
1. The biological knowledge was gathered from literature and own observations.2. The structure of the pathway was decided and converted into equations (static).3. Static model dynamic model. The model structure was analysed and
parameters optimised. Quantitative experimental data was used to compare with simulations.
4. The model was tested by simulations and new experiments –validation! etc etc.
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Sln1AspP
ATPADP
Ypd1
Ssk1AspP
Pi
high osmolarity?
Ypd1HisP
Ssk1
Sln1HisP Sln1v1
TCSv2TCS
v3TCS
v4TCS
v5TCS
Sln1
Ssk1
Hog1Glucose
DHAP
G3P
GlycerolTranslation
Gpd1, Gpp2,….
Gpd1
Gpp2
Signalpathway
Metabolism
Fps1
Osmotic stress
Osmoticstress
Glycerolextern
Plasma membrane
cytosol nucleus
Πe
Πi
MAP kinase cascade
Phospho relaysystem
Hog1
TranscriptionGPD1, GPP2,….
Gene expressionSsk2 Ssk2P
Pi
Pbs2 Pbs2P Pbs2P2
Pi
ATP ADP ATP ADP
Pi
Hog1
Ssk1
v1MAP
v2MAP
v-1MAP
v3MAP
v-2MAP v-3
MAP
ATP ADPATP ADP
Hog1P Hog1P2
Pi
ATP ADP ATP ADP
Pi
v4MAP v5
MAP
v-4MAP v-5
MAP
⊕
⊕
⊕
Hog1P2
Hog1P2nuc
mRNAnuc mRNAcyt
Proteinsnucleus
cytosol
vts
vex vrd
vpdHog1nuc
Hog1
vtrans
vtrans1
vtrans2
Glucose
Gluc-6-P
Fruc-1,6-BP
GAP DHAP
Pyruvate
Ethanol
synthesis
synthesis
3 CO2
G3P
Glycerol
NADH NAD
ADP ATP
4 NAD
4 NADH
NAD
NADH
NADH
NAD
2 ADP2 ATP NADH NAD
ATP
ADP
ATP
ADP
ATP ADP
ADP ATP
Glk1
Gpp2Gpd1
Fps1
Glucose uptake
Glycerol, ex
Phosphorelay module
MAP kinasecascade module
Gene expression module
Biophysical changes
Πi = f(Glycerol)Waterflow over membrane = f(Πi, Πe, Πt)Volume change = f(Waterflow)
(see text)
Internal osmotic pressure
External osmotic pressure
Metabolismmodule
vdephos
Ptp2vtl
v15
v14
v16
v13
v12v11
v3
v10
v1
v2
v4
v5
v6
v9
v7 v8
Edda Klipp et al, Nature Biotechnology 2005, number 8,
The High Osmolarity Glycerol (HOG) pathway in yeast
Examples of systems
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Edda Klipp et al, Nature Biotechnology 2005, number 8,
Examples of systems
32
Future perspectives
- Get answers to questions like: what happens, why does it happen and howis specificity achieved?
- To discover new principles and mechanisms for biological function
- Biotechnology: to get predictive cells
- To create a detailed model of cell regulation, focused on signal-transductioncascades. This could lead to system-level insights into mechanisms whichcould be the basis for drug discovery.
-To understand cells and eventually tissues and organs
In pharmaceutical industry: to get predictive medicines (to avoid side-effects,to individualise medicines).
Short term goal
Long term goal
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Summary – What did we learn?
- Systems biology (SB) is a scientific approach which aims at integrating biological processes into a unit. It is the study of the interactions between the components of biological systems, and how these interactions give rise to the function and behavior of that system.
- SB is the study of biological systems (at a genome-wide scale or detailed-scale)
- SB is often connected to mathematical models where theoretical models and quantitative experimental data are combined to get a system-level understanding of your biological system.
- SB offers the chance to predict the outcome of complex processes and it decreases the number of experiments (experimental planninig).
- To conduct systems biologyinvolving mathematical modeling:1) set up pathway structure based on previous knowledge (static) 2) Simulating experimental data to determine parameters 3) Predictions to test model.
- Qualitative data and quantitative data are of different types. SB drives technology forward!!!! This might be the bottle-neck today, but when we have better technologies / methods systems biology could move faster towards a promising future.
