chemodiversity/vortrag/vortrag.md

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---
title: Chemodiversity
subtitle: A short overview of this project
author: Stefan Dresselhaus
license: BSD
affiliation: Theoretic Biology Group<br>
Bielefeld University
abstract: Attempt to find indications for chemodiversity in the plant secondary metabolism according to the screening hypothesis
date: \today
papersize: a4
fontsize: 10pt
documentclass: scrartcl
margin: 0.2
slideNumber: true
...
What is chemodiversity?
-----------------------
- 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](https://doi.org/10.1098/rstb.1991.0077))
- 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](https://nph.onlinelibrary.wiley.com/doi/full/10.1111/nph.12526#nph12526-bib-0093).
--------------------------------------------------------------------------------
Setting up a simulation
=======================
>If you wish to make apple pie from scratch, you must first create the universe
> - Carl Sagan
--------------------------------------------------------------------------------
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:
```haskell
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:
![](img/compound_example.png){style="vertical-align:middle"}
- `Enzyme`{.haskell}s:
![](img/enzyme_example.png){style="vertical-align:middle"}
- `Predator`{.haskell}s:
![](img/predator_example.png){style="vertical-align:middle"}
:::
::: {.column width=63% .fragment}
![Our default test-environment](img/environment.tree.png){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
::::
--------------------------------------------------------------------------------
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
--------------------------------------------------------------------------------
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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