chemodiversity/vortrag/vortrag.md

title	subtitle	author	license	affiliation	abstract	date	papersize	fontsize	documentclass	margin	slideNumber
Chemodiversity	A short overview of this project	Stefan Dresselhaus	BSD	Theoretic Biology Group<br> Bielefeld University	Attempt to find indications for chemodiversity in the plant secondary metabolism according to the screening hypothesis	\today	a4	10pt	scrartcl	0.2	true

• It was observed, that many plants seem to produce many compounds with no obvious purpose
• Using resources to produce such compounds (instead of i.e. growing) should yield a fitness-disadvantage
• one expects evolution to eliminate such behavior

Question: Why is this behavior observed?

• Are these compounds necessary for some unresearched reason?
  • unknown environmental effects?
  • unknown intermediate products for necessary defenses?
  • speculative diversity because they could be useful after genetic mutations?

Screening Hypothesis

• First suggested by Jones & Firn (1991)
• new (random) compounds are rarely biologically active
• plants have a higher chance finding an active compound if they diversify
• many (inactive) compounds are sustained for a while because they may be precursors to biologically active substances

. . .

There are indications for and against this hypothesis by various groups.

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Setting up a simulation

If you wish to make apple pie from scratch, you must first create the universe

• Carl Sagan

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Defining Chemistry

• First of all we define the chemistry of our environment, so we know all possible interactions and can manipulate them at will.
• We differentiate between Substrate{.haskell} and Products{.haskell}:
  • Substrate{.haskell } can just be used (i.e. real substrates if the whole metabolism should be simulated, PPM{.haskell}^[1]^ in our simplified case)
  • Products{.haskell } are nodes in our chemistry environment.
• In Code:

  data Compound = Substrate Nutrient
                | Produced Component
                | GenericCompound Int
  

::: footer ^[1]^: plants primary metabolism :::

Usage in the current Model

• The Model used for evaluation just has one Substrate{.haskell}:
  PPM{.haskell} with a fixed Amount to account for effects of sucking primary-metabolism-products out of the primary metabolic cycle
• This is used to simulate i.e. worse growth, fertility and other things affecting the fitness of a plant.
• We are not using named Compounds, but restrict to generic Compound 1{.haskell}, Compound 2{.haskell} ...
• Not done, but worth exploring:
  • Take a "real-world" snapshot of Nutrients and Compounds and recreate them
  • See if the simulation follows the real world

Defining a Metabolism

• We define Enzyme{.haskell}s as

  • having a recipe for a chemical reaction
  • are reversible
  • may have dependencies on catalysts to be present
  • may have higher dominance over other enzymes with the same reaction

• Input can be Substrate{.haskell} and/or Products{.haskell}

• Outputs can only be Products{.haskell}

• \Rightarrow This makes them to Edges in a graph combining the chemical compounds

Usage in the current Model

• Enzyme{.haskell}s all
  • only map 1{.haskell} input to 1{.haskell} Output with a production rate of 1{.haskell} per Enzyme{.haskell}
    (i.e. -1 Compound 2 -> +1 Compound 5{.haskell})
  • are equally dominant
  • need no catalysts

Defining Predators

• Predator{.haskell}s consist of
  • a list of Compound{.haskell}s that can kill them
  • a fitness impact ([0..1]) as the probability of killing the plant
  • an expected number of attacks per generation
  • a probability ([0..1]) of appearing in a single generation
• Predator{.haskell} need not necessary be biologically motivated
  • i.e. rare, nearly devastating attacks (floods, droughts, ...) with realistic probabilities

Example Environment

:::::::::::::: {.columns}

::: {.column width=37%}

• The complete environment now consists of
  • Compound{.haskell}s:
    {style="vertical-align:middle"}
  • Enzyme{.haskell}s:
    {style="vertical-align:middle"}
  • Predator{.haskell}s:
    {style="vertical-align:middle"}

:::

::: {.column width=63% .fragment}

{width=75%}

Additional rules:

• Every "subtree" from the marked PPM{.haskell} is treated as a separate species (fungi, animals, ...)
  \Rightarrow Every predator can only be affected by toxins in the same part of the tree
• Trees can be automatically generated in a decent manner to search for environmens where specific effects may arise :::

::::::::::::::

::::: notes :::::

CTRL+Click for zoom!

• All starts at PPM (Plant Primary Metabolism)
• Red = Toxic
• Blue = Predators

::::

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Plants

A plant consists of ...

Metabolism simulation

Compounds are created foo..

Fitness

• Static costs of enzymes
• Cost of active enzymes

Attacker

• Rate of attack ~> Paper, Formulas
• Defenses
  • single plant
  • automimicry

Haploid mating

• fixed population-size (100)
• p(\textrm{reproduction}) = \frac{\textrm{plant-fitness}}{\textrm{total fitness in population}}
• Gene
  • mutation
  • duplication
  • deletion
  • addition
  • activation-noise

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Simulations

Parameters tested

• x
• y
• z

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Results

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.

• Richard P. Feynman

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