Simulating genes operation and Simulating genes operation and interactioninteraction
Rekubratsky V.A., Korotkova M.A.
Cetre “Bioengineering” RASMoscow Physical Engineering Institure (State University)
1. 1. Introducing into the area of Introducing into the area of interestinterest
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Basic concepts
1. Gene
2. Gene operation
3. Genes interaction
4. Gene network
5. Gene network representation
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1. Gene
• Hereditary (inheritance) information unit• Defines every organism development
• What does ‘genes operation’ mean?
Organisms development
Genes operation
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2. Gene operation (gene activity)
Responsible for producing its special protein
Protein amount is the characteristic that can be measured
Production rate varies from cell to cell
What does it depend on?
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3. Genes interaction
• Some proteins can have positive or negative influence on production rates of other proteins
• This is the way genes can ‘interact’ with each other
• May occur within one cell or throughout a part of organism
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4. Gene network
• System of gene interactions
• Usually represented by a directed graph:– Vertices represent genes– Arcs represent interaction facts
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5. Gene network representation
gene B activates gene A (positive interaction)
A B
gene B suppresses gene A (negative interaction)
A B
Real network exampleElementary interactions
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Importance of study
Organisms development
Genes operation: gene -> protein
Genes interaction (network)
2. 2. Problem statementProblem statement
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Problems of gene network representation
• No dynamics• No cell localization of interaction processes
• Hard to test• Hard to verify conformity with experimental
data
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Computer simulation system to be designed:
• Simulates genes operation and interaction in a multicellular organism basing on gene network graph
• Thus verifies conformity with experimental data
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Computer simulation system to be designed:
• Takes cell localization of interaction processes into consideration
• Enables explicit manipulation of gene operation
CLV1+2
CLV3
WUS
cell division
cell divisionCLV3 CLV1+2
WUSdivision
3. 3. Simulation systemSimulation system
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Levels of abstraction
gene1gene1gene2
geneM
param1param2
... ...paramN
gene1
gene2
geneM
...
cell vital activity or interaction processes
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Gene model• Outer state – amount of protein• Inner state – protein generation ability• Speed of protein degradation (gradual decrease of
protein amount)• Block flag – to manipulate gene operation explicitly
Outer state
Inner state
operate
block+
- degradation
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• Universal mechanism of describing both vital activity and interaction processes
Interaction rules
2. Parameter changes
3. Priority, radius of action,
duration
1. Conditions
Rule of interaction
Interaction processes
- gene interactions,- cell substances transport ...
Vital activity processes
- growth, - division,- tissue differentiation ...
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Cell group structure
• System’s main orientation is simulation of plant development
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Cell group structure
• Hemisphere structure is an approximation to plant’s cell group giving birth to the whole upper part of plant
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Cell group structure
• However, the structure can be used for simulation of many other vital processes in different organisms
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Simulation flow
• Step-by-step
• Each step corresponds to one cell group state:– cell group structure– cell parameters– gene parameters
4. 4. Program implementationProgram implementation
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Operation steps1. Setting up gene
network & interaction rules
2. Setting up initial cell group state &
structure parameters
4. Results analysis 3. Simulating, parameters modifying
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Interface tendencies
• Simplification:– Network creation similar to common drawing– Use of algebraic notation in interaction rule
expressions
• Visual aids– 3D model of cell structure– Graphical indication of simulation flow details– Graphs for cell and gene parameters
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Extensibility
• Multilevel architecture
• Use of design patterns
• Cross platform– OpenGL– MFC => wxWidgets– Program core (most part of code) is platform-
independent
55. . Test resultsTest results
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Cell growth and division
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Gene interaction loop with negative feedback
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Genetic control of stem growth of Arabidopsis thaliana plant
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HCV (hepatitis C virus) development and cell infection
66. . NoveltyNovelty
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System advantages comparing to analogs
• For gene network simulation :– takes cell localization of interaction processes into
consideration
• For all-purpose simulation:– a simpler interface, does not demand programming
skills from a user
77. . ConclusionsConclusions
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System demonstrates:
• Adequacy to simulate gene network operation in multicellular structures
• Universality to describe large variety of cell interaction and vital activity processes
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Perspectives and plans
• Development of approaches and algorithms to solve inverse problem
• Transformation into totally cross-platform system
• Further interface simplification
The work is supported by Science & Technology International Park “Technopark
in Moskvorechje” along with “UMNIK” program
Thank you for your attentionThank you for your attention
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