256 lines
6.4 KiB
Markdown
256 lines
6.4 KiB
Markdown
---
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title: Chemodiversity
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subtitle: A short overview of this project
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author: Stefan Dresselhaus
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license: BSD
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affiliation: Theoretic Biology Group<br>
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Bielefeld University
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abstract: Attempt to find indications for chemodiversity in the plant secondary metabolism according to the screening hypothesis
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date: \today
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papersize: a4
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fontsize: 10pt
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documentclass: scrartcl
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margin: 0.2
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slideNumber: true
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...
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What is chemodiversity?
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-----------------------
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- It was observed, that many plants seem to produce many compounds with no
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obvious purpose
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- Using resources to produce such compounds (instead of i.e. growing) should
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yield a fitness-disadvantage
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- one expects evolution to eliminate such behavior
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Question: Why is this behavior observed?
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--------------------------------
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- Are these compounds necessary for some unresearched reason?
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- unknown environmental effects?
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- unknown intermediate products for necessary defenses?
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- speculative diversity because they could be useful after genetic mutations?
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Screening Hypothesis
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--------------------
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- First suggested by Jones & Firn ([1991](https://doi.org/10.1098/rstb.1991.0077))
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- new (random) compounds are rarely biologically active
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- plants have a higher chance finding an active compound if they diversify
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- many (inactive) compounds are sustained for a while because they may be
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precursors to biologically active substances
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. . .
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There are indications for and against this hypothesis by [various groups](https://nph.onlinelibrary.wiley.com/doi/full/10.1111/nph.12526#nph12526-bib-0093).
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--------------------------------------------------------------------------------
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Setting up a simulation
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=======================
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>If you wish to make apple pie from scratch, you must first create the universe
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> - Carl Sagan
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--------------------------------------------------------------------------------
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Defining Chemistry
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------------------
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- First of all we define the chemistry of our environment, so we know all possible
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interactions and can manipulate them at will.
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- We differentiate between **`Substrate`{.haskell}** and
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**`Products`{.haskell}**:
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- **`Substrate`{.haskell
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}** can just be used (i.e. real substrates if the whole metabolism
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should be simulated, **`PPM`{.haskell}**^[1]^ in our simplified case)
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- **`Products`{.haskell
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}** are nodes in our chemistry environment.
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- In Code:
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```haskell
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data Compound = Substrate Nutrient
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| Produced Component
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| GenericCompound Int
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```
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::: footer
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^[1]^: plants primary metabolism
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:::
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Usage in the current Model
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--------------------------
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- The Model used for evaluation just has one `Substrate`{.haskell}:
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`PPM`{.haskell} with a fixed Amount to account for effects of sucking
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primary-metabolism-products out of the primary metabolic cycle
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- This is used to simulate i.e. worse growth, fertility and other things
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affecting the fitness of a plant.
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- We are not using named Compounds, but restrict to generic `Compound
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1`{.haskell},
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`Compound 2`{.haskell} ...
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- Not done, but worth exploring:
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- Take a "real-world" snapshot of Nutrients and Compounds and recreate them
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- See if the simulation follows the real world
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Defining a Metabolism
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---------------------
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- We define **`Enzyme`{.haskell}s** as
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- having a recipe for a chemical reaction
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- are reversible
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- may have dependencies on catalysts to be present
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- may have higher dominance over other enzymes with the same reaction
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- Input can be `Substrate`{.haskell} and/or `Products`{.haskell}
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- Outputs can only be `Products`{.haskell}
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- $\Rightarrow$ This makes them to Edges in a graph combining the chemical
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compounds
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Usage in the current Model
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--------------------------
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- `Enzyme`{.haskell}s all
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- only map `1`{.haskell} input to `1`{.haskell} Output with a production rate of `1`{.haskell} per `Enzyme`{.haskell}
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(i.e. `-1 Compound 2 -> +1 Compound 5`{.haskell})
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- are equally dominant
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- need no catalysts
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Defining Predators
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------------------
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- **`Predator`{.haskell}s** consist of
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- a list of `Compound`{.haskell}s that can kill them
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- a fitness impact ($[0..1]$) as the probability of killing the plant
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- an expected number of attacks per generation
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- a probability ($[0..1]$) of appearing in a single generation
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- `Predator`{.haskell} need not necessary be biologically motivated
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- i.e. rare, nearly devastating attacks (floods, droughts, ...) with realistic
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probabilities
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Example Environment
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-------------------
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:::::::::::::: {.columns}
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::: {.column width=37%}
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- The complete environment now consists of
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- `Compound`{.haskell}s:
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![](img/compound_example.png){style="vertical-align:middle"}
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- `Enzyme`{.haskell}s:
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![](img/enzyme_example.png){style="vertical-align:middle"}
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- `Predator`{.haskell}s:
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![](img/predator_example.png){style="vertical-align:middle"}
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:::
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::: {.column width=63% .fragment}
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![Our default test-environment](img/environment.tree.png){width=75%}
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Additional rules:
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- Every "subtree" from the marked `PPM`{.haskell} is treated as a separate
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species (fungi, animals, ...)
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$\Rightarrow$ Every predator can only be affected by toxins in the same part of the tree
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- Trees can be automatically generated in a decent manner to search for
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environmens where specific effects may arise
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:::
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::::::::::::::
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::::: notes :::::
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CTRL+Click for zoom!
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- All starts at PPM (Plant Primary Metabolism)
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- Red = Toxic
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- Blue = Predators
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::::
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--------------------------------------------------------------------------------
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Plants
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------
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A plant consists of
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...
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Metabolism simulation
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---------------------
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Compounds are created foo..
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Fitness
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-------
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- Static costs of enzymes
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- Cost of active enzymes
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Attacker
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--------
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- Rate of attack ~> Paper, Formulas
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- Defenses
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- single plant
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- automimicry
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Haploid mating
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--------------
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- fixed population-size (100)
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- $p(\textrm{reproduction}) = \frac{\textrm{plant-fitness}}{\textrm{total fitness in population}}$
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- Gene
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- mutation
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- duplication
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- deletion
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- addition
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- activation-noise
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--------------------------------------------------------------------------------
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Simulations
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-----------
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Parameters tested
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- x
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- y
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- z
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--------------------------------------------------------------------------------
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Results
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=======
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>It doesn't matter how beautiful your theory is, it doesn't matter how smart you are. If it doesn't agree with experiment, it's wrong.
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> - Richard P. Feynman
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--------------------------------------------------------------------------------
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